Health and lifestyle prediction

ABSTRACT

A detection system is provided for a distributed water infrastructure to determine a human health or lifestyle state from detected water usage patterns. The system receives signals indicative of water usage from at least one sensor upstream of a plurality of appliances, and determines from the signals a current water usage pattern. The system accesses a database of a plurality of stored water usage patterns, associated with a human health or lifestyle state, compares the pattern with stored water usage patterns and, based on the comparison, identifies a human health or lifestyle condition reflected by the current water usage pattern.

CLAIM FOR PRIORITY

This application claims benefit of priority of U.S. Provisional PatentApplication No. 62/425,494, filed Nov. 22, 2016, which is incorporatedherein by reference in its entirety.

TECHNICAL FIELD

The present disclosure may be related to devices, systems, and methodsfor detecting the usage of liquids and initiating appropriate remedialactions. More particularly, part of the disclosure may be directed toidentifying specific types of liquid usage and initiating appropriateremedial action.

BACKGROUND

A distributed water infrastructure may include any arrangement ofconduits for supplying plumbing fixtures, appliances, storage devices,treatment devices, or any other device that receives water. For example,a distributed water infrastructure may include the pipes and/or otherconduits of a city, a neighborhood, a complex of buildings, a building,a floor, and a room. A distributed water infrastructure may also includea collection of conduits within a room. In an industrial, commercial, orresidential setting, the conduits in individual areas of a single floormight each be considered a separate distributed water infrastructure.Alternatively, multiple contiguous or non-contiguous conduits might beconsidered a single distributed water infrastructure.

The distributed water infrastructure may be essential to many commercialand private activities. The continued use of a distributed waterinfrastructure runs the risk of leaks and the unknowing waste of water.In some instances, users of a distributed water infrastructure do notrealize a leak is occurring until it is too late to prevent damage tobuildings and the waste of large amounts of water. In many instances,users may not know how water in a distributed water infrastructure isbeing used, and are unable to discern what are the sources of waterwaste if the leaks are slow. At times, the process of determining whatappliance may be leaking may be difficult.

Because it can be difficult to know how water is being used, thereremains an opportunity to track water to determine if water is stolen orwasted. As water is essential to human health, greater information onthe use of water may also enable the ability to check on the health ofremote persons, to see if they are alive, brushing their teeth, or doingother health-related activities. Additional detail about various waterusage by employing high resolution sensors may provide solutions tothese problems.

It may therefore be desirable to employ methods and systems formonitoring the use of water in a distributed water infrastructure. Sucha system may enable greater control over a property's water system, mayenable greater water savings by reducing unnecessary expenses, and mayenable better alerts regarding any potentially damaging water situation.

SUMMARY

The present disclosure generally relates to a system for detecting flowof a fluid. While the present disclosure provides examples of detectingwater flow, it should be noted that aspects of the disclosure in theirbroadest sense, are not limited only to systems for detecting waterflow. Rather, it may be contemplated that the forgoing principles may beapplied to other fluids as well, including gases and liquids other thanwater.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for detecting abnormal consumption in adistributed water infrastructure. The system may receive from at leastone sensor associated with the distributed water infrastructure signalsindicative of water usage in the distributed water infrastructure, andaggregate groups of signals to construct a plurality of time-based waterevent profiles, each water event profile containing a distribution ofwater usage indicators over time. The system may store a subset of theplurality of water event profiles in memory as normal water eventprofiles, and receive, from the at least one sensor, signals indicativeof current water usage in the distributed water infrastructure. Thesystem may construct, from the signals indicative of current waterusage, at least one current water event profile, and compare the atleast one current water event profile with normal water event profilesstored in the memory. The system may initiate remedial action if the atleast one current water event profile does not substantially correspondto normal water event profiles stored in the memory.

Exemplary embodiments of the present application provide for, but arenot limited to, an abnormal consumption detection system for adistributed water infrastructure. The system may comprise anelectronically controllable valve, a remote communication transmitter, aremote communication receiver, at least one consumption sensor formeasuring water flow information associated with the distributed waterinfrastructure, and at least one processor. The system may determinefrom the water flow information obtained from the at least oneconsumption sensor a potential abnormal consumption associated with thedistributed water infrastructure. The system may automatically close avalve, without human intervention, when the potential abnormalconsumption is determined. The system may transmit, via the remotecommunication transmitter to a remote administrator, alert informationabout the potential abnormal consumption to enable an administrator todecide based on the transmitted information whether to reopen the valve.The system may receive from the administrator via the remotecommunication receiver a control signal to reopen the valve, despite theinformation about the potential abnormal consumption, and reopen thevalve.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for detecting abnormal consumption in oneportion of a distributed water infrastructure while normal water usageoccurs in another portion of the distributed water infrastructure. Thesystem may comprise at least one processor. The system may receive fromat least one sensor associated with the distributed water infrastructureindications of regular water usage. The system may determine, from aplurality of indications received over a time period, a plurality ofbaseline water usage profiles. The system may receive from the at leastone sensor a current water usage profile. The system may compare thecurrent water usage profile with the plurality of baseline water usageprofiles. The system may determine an abnormal water consumption basedon the comparison between the current water usage profile and theplurality of baseline water usage profiles. The system may generate anabnormal water consumption signal when abnormal water consumption isdetermined.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for detecting abnormal consumption in adistributed water infrastructure. The system may comprise at least oneprocessor. The system may receive from at least one sensor associatedwith the distributed water infrastructure indications of regular waterusage, wherein the distributed water infrastructure includes a pluralityof water appliances. The system may determine from the indicationsreceived over a time period, at least one recurring time period ofexpected diminished water usage. The system may determine for the atleast one recurring time period of expected diminished water usage atleast one expected diminished water usage profile. The system mayreceive from the at least one sensor during a current time period ofexpected diminished water usage, real time indications of water usage,which may constitute a current water usage profile. The system maycompare the current water usage profile during the expected period ofdiminished water usage with the at least one expected diminished waterusage profile. The system may, based on the comparison, determine thatwater usage in the current water usage profile materially exceeds waterusage in the at least one expected water usage profile. The system mayexecute a remedial action when, based on the comparison, the currentwater usage profile materially exceeds the at least one expected waterusage profile.

Exemplary embodiments of the present application provide for, but arenot limited to, a detection system for a distributed waterinfrastructure, wherein the system is configured to determine at leastone of a human health or lifestyle state from water usage patterns inthe distributed water infrastructure. The system may comprise at leastone processor. The system may receive from at least one sensorassociated with the distributed water infrastructure signals indicativeof water usage in the distributed water infrastructure. The system maydetermine from the signals indicative of water usage a current waterusage pattern. The system may access a database of a plurality of storedwater usage patterns, wherein each at least one stored water usagepattern is associated with at least one human health or lifestyle state.The system may compare at least one current water usage pattern with atleast some of the stored water usage patterns. The system may, based onthe comparison, identify a human health or lifestyle condition reflectedby the current water usage pattern. The system may institute a remedialaction corresponding to the identified human health or lifestyle state.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for differentiating between overlapping waterevents in a distributed water infrastructure including a plurality ofwater appliances. The system may comprise at least one processor. Thesystem may repeatedly measure at least one overall water usage indicatorof the distributed water infrastructure, the at least one water usageindicator including at least one of an overall flow rate and an overallflow volume in the distributed water infrastructure. The system maydetect, in the repeated measurements, a first sustained increase. Thesystem may store in memory a first indicator of the first sustainedincrease. The system may attribute in memory the first sustainedincrease to a first water event in the distributed water infrastructure.The system may, during the first sustained increase, detect in theoverall measurements a second sustained increase. The system may storein memory a second indicator of the second sustained increase. Thesystem may attribute, in memory, the second sustained increase to asecond water event in the distributed water infrastructure. The systemmay detect, following initiation of the first sustained increase and thesecond sustained increase, in the repeated measurements a decrease inthe overall water usage indicator. The system may attribute to thedecrease a third indicator. The system may compare the third indicatorwith at least one of the first indicator and the second indicator storedin memory to determine a substantial match and determine a cessation ofat least one of the first water event and the second water event. Thesystem may initiate an action based on the cessation determination.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for tracking usage of a plurality of waterappliances in a distributed water infrastructure. The system maycomprise at least one processor. The system may receive, from a locationin the distributed water infrastructure upstream of the plurality ofwater appliances, historical water usage measurements. The system maydetermine from the historical water usage measurements at least oneunique water usage signature associated with each of the plurality ofwater appliances. The system may store in memory each at least oneunique water usage signature for each of the plurality of appliances.The system may receive, from the location in the distributed waterinfrastructure upstream of the plurality of water appliances, currentwater usage measurements. The system may determine from the currentwater usage measurements at least one current water usage signature. Thesystem may compare the current water usage signature with at least oneof the unique water usage signatures stored in memory to determine amatch. The system may, based on the signature match, ascertain anidentifier of a water appliance in current use.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for determining operational states of specificcategories of water appliances using a plurality of geographicallydistributed water sensors. The system may comprise at least one centralprocessor. The system may receive water appliance usage data from theplurality of geographically distributed water sensors, wherein eachwater sensor is located upstream of a plurality of water appliances inan associated distributed water infrastructure, and wherein each watersensor is configured to collect data from an infrastructure inlet flowreflective of operation of at least one specific category of waterappliance downstream of the water sensor. The system may compare thewater appliance usage data from the plurality of geographicallydistributed water sensors to determine trends in operation of the atleast one specific category of water appliance across a population. Thesystem may output information about the trends in operation.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for determining from a location upstream of aplurality of water appliances, whether a specific water appliance ismalfunctioning. The system may comprise at least one processor. Thesystem may detect, from at least one sensor in a distributed waterinfrastructure upstream of the plurality of water appliances, aplurality of normal water usage profiles. The system may associate atleast one of the plurality of normal water usage profiles with each ofthe plurality of water appliances. The system may store each of theplurality of normal water usage profiles in a manner associating each ofthe plurality of normal water usage profiles with an associated waterappliance. The system may detect at least one current water usageprofile. The system may compare the at least one current water usageprofile with at least one of the stored normal water usage profiles todetermine a corresponding identity of an associated water usageappliance and to determine if a substantial deviation exists between thestored normal water usage profile for the identified appliance and theat least one current water usage profile. The substantial deviation maybe reflective of a potential malfunction in the associated water usageappliance. The system may initiate remedial action if the substantialdeviation, reflective of a potential malfunction, is determined.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for tracking, in a distributed waterinfrastructure, water usage by category. The system may comprise atleast one processor. The system may receive from at least one sensorassociated with the distributed water infrastructure signals indicativeof water usage in the distributed water infrastructure. The system may,based on the signals indicative of water usage, construct a plurality ofprofiles. The system may assign each profile to one of a plurality ofwater usage categories. The system may collect, from the at least onesensor, signals indicative of water usage for substantially all waterdelivered through the distributed water infrastructure in a time period.The system may construct a plurality of water usage profiles in theaggregate, encompassing substantially all water delivered through thedistributed water infrastructure in the time period. The system mayassign each constructed water usage profile to one of the plurality ofwater usage categories. The system may output, for display, water usagefor the time period for each of the plurality of water usage categories.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for differentiating between water usage ofmultiple water consumers using a common distributed waterinfrastructure. The system may comprise at least one processor. Thesystem may receive from a water sensor in the distributed waterinfrastructure upstream of a plurality of appliances, signals indicativeof water usage. The system may construct from the signals indicative ofwater usage a plurality of water event profile signatures. The systemmay, based on differences between similar water event profiles,associate at least one water event profile signature with a first waterconsumer and associate a second water event profile signature with asecond water consumer. The system may store the water event profilesignatures for the first water consumer and the second water consumer.The system may construct current water event profiles reflectingsubsequent water usage in the distributed water infrastructure. Thesystem may compare the current water event profiles with water eventprofile signatures stored in memory. The system may, based on thecomparison, attribute a first current water event profile to the firstwater consumer and attribute a second current water event profile to thesecond water consumer. The system may output data for generating atleast one report of water usage by the first water consumer.

Exemplary embodiments of the present application provide for, but arenot limited to, an electronic sensing and allocation system for adistributed water infrastructure containing a plurality of differingappliances. The system may comprise at least one processor. The systemmay receive, from at least one sensor upstream of the plurality ofdiffering appliances, a plurality of signals indicative of water usagewithin the distributed water infrastructure. The system may extract,from the plurality of signals, first information identifying a volume ofwater usage of at least a first appliance. The system may attribute afirst volume of water to a first category. The system may extract, fromthe plurality of signals, second information identifying a volume ofwater usage of at least a second appliance. The system may attribute asecond volume of water to a second category, wherein a first rateschedule is applicable to the first category, and a second rateschedule, other than the first rate schedule, is applicable to thesecond category. The system may output a first indication of the firstvolume of water together with an indicator attributing the first volumeof water to the first rate schedule, and output a second indication ofthe second volume of water together with an indicator attributing thesecond volume of water to the second rate schedule. The system mayenable billing of the first and second volumes of water to a consumer atdiffering rates based on differing uses.

Exemplary embodiments of the present application provide for, but arenot limited to, a system for monitoring water usage of a plurality ofappliances in a plurality of distributed locations remote from oneanother. The system may comprise at least one central processor. Thesystem may receive water usage data from the plurality of distributedlocations. The system may determine, from the water usage data receivedfrom the plurality of distributed locations, a common appliance used ineach of the plurality of distributed locations. The system may analyze asubset of the water usage data attributable to the common appliance todetermine usage patterns associated with the common appliance across theplurality of distributed locations. The system may output usage patternanalytics associated with the common appliance.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an exemplary distributed water infrastructure.

FIGS. 2a and 2b illustrate exemplary systems for detecting theconsumption of liquids.

FIG. 3 illustrates an exemplary method for detecting the consumption ofliquids.

FIGS. 4a and 4b illustrate exemplary systems for remote valve reopeningand/or automatic valve closure after the detection of abnormalconsumption.

FIG. 5a illustrates an exemplary method for remote valve reopeningand/or automatic valve closure after the detection of abnormalconsumption.

FIG. 5b illustrates an exemplary method for remote valve reopeningand/or automatic valve closure after the detection of abnormalconsumption including an option to ignore warnings of abnormalconsumption.

FIG. 6 illustrates an exemplary method for detecting abnormalconsumption in a portion of a distributed water infrastructure.

FIG. 7 illustrates an exemplary method for detection of abnormalconsumption with low volumes of water consumption.

FIG. 8a illustrates an exemplary method for estimating a health andlifestyle status based on water consumption.

FIG. 8b illustrates an exemplary water usage pattern for detecting ahandwashing state after the use of a toilet.

FIG. 9 illustrates an exemplary method for differentiating betweenoverlapping water events in a distributed water infrastructure with aplurality of water appliances.

FIGS. 10a-g illustrate exemplary water usage patterns over time, withflow rate on the y-axis and time on the x-axis.

FIG. 11 illustrates an exemplary method for tracking usage of aplurality of water appliances in a distributed water infrastructure.

FIG. 12a illustrates an exemplary method for determining operationalstates of categories of water appliances using a plurality ofgeographically distributed water sensors.

FIG. 12b illustrates an exemplary system for determining operationalstates of categories of water appliances using a plurality ofgeographically distributed water sensors.

FIG. 13 illustrates an exemplary method for determining, from a locationupstream of a plurality of water appliances, whether a specific waterappliance may be malfunctioning.

FIG. 14 illustrates an exemplary method for tracking, in a distributedwater infrastructure, water usage by category.

FIG. 15 illustrates an exemplary method for differentiating betweenwater usage of multiple water consumers using a common distributed waterinfrastructure.

FIG. 16 illustrates an exemplary method of electronic sensing andallocation for a distributed water infrastructure containing a pluralityof differing appliances.

FIG. 17 illustrates an exemplary method for monitoring water usage of aplurality of appliances in a plurality of distributed locations remotefrom one another.

FIG. 18 illustrates an exemplary graphical user interface for a systemthat may remotely control a valve and track water usage.

FIG. 19a illustrates an exemplary system for detecting consumption ofliquids.

FIG. 19b illustrates an exemplary system for detecting consumption ofliquids where data processing and data storage occur in the cloud.

FIG. 19c illustrates an exemplary system for detecting consumption ofliquids where an end device performs data collection and transmission,and data processing and data storage occur in the cloud.

DETAILED DESCRIPTION

Exemplary embodiments of the present application are described infurther detail below.

Definition of Terms

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art. In case of conflict, the present document, includingdefinitions, will control. Preferred methods and materials are describedherein, although methods and materials similar or equivalent to thosedescribed herein can be used in practice or testing of embodiments ofthe present disclosure. The materials, methods, and examples disclosedherein are illustrative only and not intended to be limiting.

The terms “comprise(s),” “include(s),” “having,” “has,” “can,”“contain(s),” and variants thereof, as used herein, are intended to beopen-ended transitional phrases, terms, or words that do not precludethe possibility of additional acts or structures. The singular forms“a,” “an,” and “the” include plural references unless the contextclearly dictates otherwise. The present disclosure also contemplatesother embodiments “comprising,” “consisting of,” and “consistingessentially of” the embodiments or elements presented herein, whetherexplicitly set forth or not.

The conjunctive term “or” may include any and all combinations of one ormore listed elements associated by the conjunctive term. For example,the phrase “an apparatus comprising a or b” may refer to an apparatusincluding a where b may be not present, an apparatus including b where amay be not present, or an apparatus where both a and b are present. Thephrases “at least one of a, b, . . . , and n” or “at least one of a, b,. . . , n, or combinations thereof” are defined in the broadest sense tomean one or more elements selected from the group comprising a, b, . . ., and n, that is to say, any combination of one or more of the elementsa, b, . . . , or n including any one element alone or in combinationwith one or more of the other elements, which may also include, incombination, additional elements not listed.

The terms “first,” “second,” “third,” and the like, as used herein, donot denote any order, quantity, or importance, but rather are used todistinguish one element from another.

The term “substantially,” as used herein, represents the inherent degreeof uncertainty that may be attributed to any quantitative comparison,value, measurement, or other representation. The term “substantially”may be also utilized herein to represent the degree by which aquantitative representation may vary from a stated reference withoutresulting in a change in the basic function of the subject matter atissue.

The term “water consumer,” as used herein, represents both waterappliances and people that consume water. It may also be a combinationof the two. Water consumers may use water directly or indirectly.

The term “system,” as used herein, may include both hardware andsoftware that can either work in tandem or independently. The system canbe located locally or in the cloud or a combination of each.

The term “sensor,” as used herein, represents a device that provides anoutput reflective of the water usage, such as flow rate, and the waterproperties like temperature, pressure, etc. A sensor can be a mechanicalsensor such as a multi-jet sensor, positive displacement sensor,ultrasonic sensor, binary sensor (capable of detecting presence orabsence of liquid, e.g. a humidity detector) or any other instrumentcapable of outputting a signal reflecting the presence of liquid flow.At least one sensor can be one, two, or a plurality of sensorsregardless of whether they are in a common location or in variouslocations.

The term “signals indicative of water usage” or “water usage pattern” asused herein, represents any electronic representation of a propertyassociated with the flow of water (or in a more general sense liquid).Such signals might include an electronic representation of flow, volume,pressure, velocity, or any combination thereof. Thus, a signalindicative of water usage may include any output of at least one sensor.An output of a flow sensor, digital signal, analog signal, and wire orwireless signal, may be any output that correlates to the liquid flow.

The term “substantial deviation” as used herein refers to a measurementof deviation from the normal expected usage for each water-usingappliance. A substantial deviation from the normal expected usage canhelp determine proper usage and efficiency of the water-using appliance.In some embodiments, a substantial deviation may be greater than astandard deviation of at least one characteristic of normal expectedusage for a water-using appliance. A substantial deviation may begreater than some preset value. A substantial deviation may be a learnedvalue determined by a machine learning algorithm.

The term “noise” or “acoustic noise” as used herein refers tofluctuations in a signal. Noise may refer to an acoustic sound. Noisemay refer to errors associated with the signal to noise ratio of asensor. Noise may also refer to random fluctuations in a water flow ratethat are associated with the flow of water through a distributed waterinfrastructure. Certain water consumers may generate noise of differentmagnitude and/or different frequencies.

Although pressure and fluid flow rate are theoretically relatedaccording to Poiseuille's law, the validity of this law may be based onassumptions that typically may not hold in real-world conditions thatprevail in distributed water infrastructures. For example, Poiseuille'slaw assumes laminar flow of a Newtonian fluid within a cylindrical pipeof constant cross section. In real-world branched pipeline fluiddistribution systems, however, fluid flow may be turbulent andexperience acceleration (and deceleration). A measurement of fluid flowmay therefore provide opportunities to have superior resolution over ameasurement of pressure.

Inventive concepts may include one or more of the following, eitheralone or in combination with other disclosed embodiments. Moreover, itis contemplated that the components of each of the following embodimentscan be combined with one or more components of other disclosedembodiments, and therefore, the specific combinations discussed hereinare not to be considered restrictive or exclusive.

Exemplary Embodiments of Event-Based Leak Detection

The present application provides for leak detection during normal waterusage. A potential benefit of some embodiments of the present disclosureinclude their ability to detect abnormal consumption, even during timesof normal water usage. Systems and methods of the present disclosure maybe enabled to do so by determining a baseline of existing usage, andthen ascertaining a non-expected deviation from the baseline. Inaddition or in the alternative, systems and methods may be able toidentify the use of water at a granular level, such that normal waterusage may be categorized into discrete events, and the addition of a newunrecognized event may indicate a leak.

An aspect of some embodiments may include a system for detectingabnormal consumption of water in a distributed water infrastructure.FIG. 1 illustrates an exemplary distributed water infrastructure 100.Distributed water infrastructure 100 may include any arrangement ofconduits 110 for supplying plumbing fixtures, appliances, storagedevices, treatment devices, or any other device that receives water.

A distributed water infrastructure may have a single inlet, indicated byinlet 111. A distributed water infrastructure may include a singlehousehold, indicated by water consumer 120. A distributed waterinfrastructure may include an entire building with several floors,indicated by water consumer 130. A distributed water infrastructure mayinclude a single floor within a building, indicated by water consumer140. A distributed water infrastructure may service different types ofwater users. A distributed water infrastructure may service agriculturalusers, such as for irrigation, indicated by water consumer 150. Adistributed water infrastructure may service household users, such asfor a faucet, indicated by water consumer 160. In some embodiments, eachwater consumer 120-160 may consume water in a unique manner that mayenable identification of the water consumer.

The term abnormal consumption refers generally to flow of a fluid thatdeviates from normal flow by at least one water usage indicator. A waterusage indicator may include, for example, an average flow rate, aninitial flow rate, a total volume associated with a current water event,a noise in signals indicative of water usage, and a pattern in a rate ofwater usage. The consumption of a fluid may be characterized by a waterconsumption profile. Such a profile may include a signal or a group ofsignals representative of fluid flow. By way of example, a time-basedwater event profile may include a flow rate over time that may beassociated with a particular event. Alternatively or additionally, awater event profile may include an average flow rate over time, and acharacteristic feature of a water event.

In one aspect, abnormal water consumption may be defined as a waterconsumption profile, sensed in a distributed water infrastructure, thatdeviates significantly from one or more existing water consumptionprofiles that characterize normal water consumption in a distributedwater infrastructure. An existing water consumption profile may be apre-defined profile within a library of profiles general to a variety ofdistributed water infrastructures or may be pre-learned for a specificdistributed water infrastructure. The deviation between a sensed waterconsumption profile and an existing water consumption profile may bemeasured quantitatively by comparing the sensed consumption profile witheach of the existing water consumption profiles using any suitabledistance measure of similarity or dissimilarity. The deviation of thesensed water consumption profile from an existing consumption profilemay be considered significant when the distance of the sensedconsumption profile is beyond an acceptable distance limit defined forthe existing consumption profile. Abnormal water consumption may also bedefined by a mathematical function that characterizes a known,undesirable consumption profile, which may then be compared with asensed consumption profile in order to identify an abnormality.

In accordance with the present disclosure, a system for detecting flowof a fluid may include at least one processor. The at least oneprocessor may include any physical device having an electric circuitthat performs a logic operation on input or inputs. For example, aprocessor may include one or more integrated circuits, microchips,microcontrollers, microprocessors, all or part of a central processingunit (CPU), graphics processing unit (GPU), digital signal processor(DSP), field-programmable gate array (FPGA), or other circuits suitablefor executing instructions or performing logic operations. Theinstructions executed by a processor may, for example, be pre-loadedinto a memory integrated with or embedded into the processor or may bestored in a separate memory. Memory may include a random access memory(RAM), a read-only memory (ROM), a hard disk, an optical disk, amagnetic medium, a flash memory, other permanent, fixed, or volatilememory, or any other mechanism capable of storing instructions or data.

More than one processor may be used for any function. Each processor mayhave a similar construction or the processors may be of differingconstructions that are electrically connected or disconnected from eachother. For example, the processors may be separate circuits orintegrated in a single circuit. When more than one processor is used,the processors may be configured to operate independently orcollaboratively. The processors may be coupled electrically,magnetically, optically, acoustically, mechanically, or by other meansthat permit them to interact.

In one embodiment, a processor may be a data processor, a personalcomputer, or a mainframe for performing various functions andoperations. The system for detecting abnormal consumption of water in adistributed water infrastructure may be implemented, for example, by ageneral purpose computer or a data processor selectively activated orreconfigured by a stored computer program, or may be a speciallyconstructed computing platform for carrying out the features andoperations described herein. Moreover, the system for detecting abnormalconsumption of water in a distributed water infrastructure may beimplemented or provided with a wide variety of components or systems,including one or more of the following: central processing units,co-processors, memories, registers, or other data processing devices andsubsystems.

In accordance with the present disclosure, a system for detecting flowof a fluid in accordance with the present disclosure may include atleast one sensor. A sensor may be any device that detects or measures aphysical property and records, indicates, or otherwise responds to it.For example, a sensor may provide an output reflective of water usage,such as flow rate. At least one sensor may include a mechanical sensor,such as a multi-jet sensor, a positive displacement sensor, anultrasonic sensor, or any other instrument capable of outputting asignal reflecting the presence of fluid flow. A sensor may also be adevice that provides an output reflective of water properties, such as,by way of example only, temperature, pressure, flow rate, flow volume,salinity, pH, and viscosity. At least one sensor may include a binarysensor that may be capable of detecting the presence or absence of afluid, such as a humidity detector. In other embodiments, at least onesensor may also be able to qualitatively or quantitatively measure thepresence of a bio-film. The at least one sensor may include a water flowsensor having an unmeasured flow reducer.

Some embodiments may include a water flow sensor configured to detectflow at a rate of less than about 2 liters per hour. In someembodiments, a water flow sensor may be configured to detect flow at arate of less than about 1 liter per hour. In other embodiments, a waterflow sensor may be configured to detect flow at a rate of less thanabout 0.5 liters per hour, or less than about 0.2 liters per hour.

In some embodiments, a water sensor may be an electronic orelectro-mechanical device that can detect the flow of water through adistributed water infrastructure. The water sensor may be connected toat least one processor to convey signals indicative of water usage inreal-time. The sensor itself may be based on multi-jet or ultrasonictechnology and the signals the sensor conveys to at least one processormay be quantitative, time-based values indicating flow rate or timedifference or any derivative thereof. The at least one sensor may be asingle sensor or a plurality of sensors. A plurality of sensors may bepositioned in a common location and/or may be positioned in variousseparated locations. The processor or processors that receive thesignals may be connected to the sensor locally or may be located at someremote, distributed infrastructure.

In accordance with the present disclosure, a system for detecting flowof a fluid may include at least one processor configured to receivesignals indicative of current water usage. The at least one processormay be configured to receive signals from a local sensor. In otherembodiments, the at least one processor may be configured to receivesignals from a remote sensor, through wired or wireless communication.Signals indicative of water usage may be any electronic representationof a property associated with the flow of a fluid. Signals indicative ofcurrent water usage may be signals received in real-time by at least oneprocessor from at least one sensor associated with some distributedwater infrastructure. The signals indicative of current water usage mayeach be represented by some quantitative value equivalent to the time atwhich the signal was received whether as a timestamp, or as a relativetime difference from the previous signal in the sequence, or as acumulative measure of time from a reference in time.

A signal indicative of water usage may include any output of the atleast one sensor. Such a signal may include an electronic representativeof flow, volume, pressure velocity, or any combination thereof. A signalindicative of water usage may be an output of a flow sensor, which maybe a digital or analog signal. The at least one processor may beconfigured to receive signals indicative of water usage through a wire,and may also be configured to receive signals wirelessly. The signalsindicative of water usage may be associated with a timestamp. In someembodiments, a signal may be received every time a predefined amount ofwater flows into or through the distributed water infrastructure.

In accordance with the present disclosure, a system for detecting flowof a fluid may include at least one processor configured to aggregategroups of signals. Aggregating groups of signals may include a processwhereby signals indicative of water consumption that are determined tooriginate from the same cause are grouped together into single,meaningful entities. The signals may be determined to originate from thesame cause according to some feature of the signals that may bereflective of water usage, such as flow rate, change in flow rate,volume, time difference between receiving signals, or any combinationthereof. The at least one processor may be configured to construct waterevent profiles based on at least one parameter selected from an averageflow rate, an initial flow rate, a total volume associated with acurrent water event profile, a noise in signals indicative of waterusage, and a change in the rate of water usage.

In embodiments of the present disclosure, the at least one processor maybe configured to construct a plurality of time-based water eventprofiles. Aggregated groups of signals may be transformed mathematicallyinto an alternative representation. Mathematical transformation of thegroups of signals may be any mathematical operation or function thatmaps the signals in a group of signals either individually orcollectively from one quantitative representation to anotherquantitative representation. The aggregated groups of signals may beprocessed automatically or semi-automatically in order to determine theindividual groups of signals or some combination of the groups ofsignals that represent one or more time-based water event profiles. Inthis way, a time-based water event profile may be constructed to berepresentative of water consumption that may be typical in a particulardistributed water infrastructure. In some embodiments, a plurality oftime-based water event profiles may be constructed that represent waterconsumption that may be typical in a particular distributed waterinfrastructure.

In accordance with the present disclosure, each water event profileconstructed by the at least one processor may include a distribution ofwater usage indicators over time. In some embodiments, signalsindicative of water usage may be received sequentially in time. Thesignals may be sent continuously. In other embodiments, the signals maybe sent at intervals. Individual signals may be represented by somequantitative value equivalent to the time at which the signal wasgenerated, sent, or received. For example, a quantitative valueequivalent to the time the signal was received may be a timestamp, arelative time difference since the previous signal in the sequence, or acumulative measure of time from some reference in time.

Accordingly, a time-based water event profile may be a collection oftime-based signals that have been aggregated into groups, or into groupsof groups, in a meaningful way. For example, a time-based water eventprofile may be a distribution of time-based signals over time, and maybe represented in a graph as flow rate as a function of time.

In accordance with the present disclosure, a system for detecting flowof a fluid may include at least one processor configured to store asubset of the plurality of water event profiles in memory as normalwater event profiles.

Storage may be implemented with a wide variety of systems, subsystems,and/or devices for providing memory or storage including, for example,one or more of the following: a read-only memory (ROM) device, a randomaccess memory (RAM) device, a tape or disk drive, an optical storagedevice, a magnetic storage device, a redundant array of inexpensivedisks (RAID), and/or any other device capable of providing storageand/or memory. Storage may be performed locally, or at a distantlocation. In some embodiments, physical storage may span multipleservers and locations. In some embodiments, storage services may beaccessed through a co-located cloud computer service, a web serviceapplication programming interface (API), or by applications that utilizethe API, such as cloud desktop storage, a cloud storage gateway, orweb-based content management systems.

A normal water event profile may be a water event profile that occursregularly in a distributed water infrastructure, and may berepresentative of a typical use of water. A normal water event profilemay be learned during a learning period, saved in memory, and thenprovided as a reference that characterizes the normal water consumptionin a distributed water infrastructure.

In accordance with the present disclosure, a system for detecting flowof a fluid may include at least one processor configured to receive fromthe at least one sensor, signals indicative of current water usage.Signals indicative of current water usage may be signals received inreal-time by at least one processor from at least one sensor associatedwith a distributed water infrastructure. The signals indicative ofcurrent water usage may each be represented by a quantitative valueequivalent to the time at which the signal was received, whether as atimestamp, or as a relative time difference since the previous signal inthe sequence, or as a cumulative measure of time from a reference intime.

In accordance with the present disclosure, a system for detecting flowof a fluid may include at least one processor configured to construct,from the signals indicative of current water usage, at least one currentwater event profile. The signals indicative of current water usage in adistributed water infrastructure may be grouped and transformedmathematically using the same operations described above for theplurality of water event profiles, which may have previously beenconstructed for the same distributed water infrastructure. In this way,a water event profile for the current water usage may be constructedthat is comparable to other water event profiles for the samedistributed water infrastructure.

In accordance with the present disclosure, a system for detecting flowof a fluid may include at least one processor configured to compare theat least one current water event profile with normal water eventprofiles stored in memory. The current water event profile or profilesmay be compared to each of the normal event profiles that have beenstored in memory for the distributed water infrastructure by applying asuitable mathematical operation, which may calculate a quantitativevalue for either the similarity or dissimilarity between the currentevent profile and each of the normal event profiles.

In some embodiments, a remedial action may be initiated if the at leastone current water event profile does not substantially correspond tonormal water event profiles stored in memory. Initiating remedial actionmay include providing one or more notifications to one or moreindividuals or systems. In one embodiment, the notification may be asignal provided to a processor. In another embodiment, the notificationmay be a message provided to a user, administrator, or any otherindividual. The message may be in the form of written text, graphicalillustration, or a physical signal conveyed through the distributedwater infrastructure. Written text or graphical illustrations mayprovide an indication of abnormal usage in a general sense or in aspecific sense. The notification may provide information about abnormalusage associated with a particular appliance, fixture, or other waterreceiving device, or the notification may provide general information ofa potential abnormality associated with the distributed waterinfrastructure. The notification may indicate that an appliance, such asa toilet or sink may be leaking. The notification may broadly note thata leak was detected in a distributed water infrastructure or aparticular portion of a distributed water infrastructure. In someembodiments, notifications may provide notice for events other than leakdetection. For example, a notification may be provided indicatingdegradation in the performance of an appliance, or some other variationfrom normal usage of an appliance. Some non-limiting examples ofvariations from normal usage of an appliance include a shower durationthat was longer than normal and a toilet that may be continuouslyrunning.

Notifications may be in the form of physical signals such as the pulsingof water through a distributed water infrastructure. For example, if ashower may be longer than normal, water may be pulsed to notify the userof the same. A series of pulses or a sequential series of pulses may beprovided to the user. The system may be configured to receive a replymessage from the user through the user's variance of water usage. Forexample, if the user turns off and then turns on the water, the systemmay be configured to permit continued water flow. Otherwise, if no replyis received from the user, the system may be configured to impede orfully restrict water flow.

The notifications may also include other types of physical indicatorssuch as an alarm, vibration, or a warning light. The notifications maybe provided to a mobile communication device, a telephone device, acomputer, or any other electronic instrument, such as a laptop, tablet,computer, cell phone, or smart phone. The notification may or may not beimmediately perceptible to a user. For example, remedial action mayinclude sending data to a computer system, server, wearable, or othercomputing device for later processing. As another example, notificationsmay be collected in a system and then a report may be generatedsummarizing the notifications. Alternatively, once a number ofnotifications has accumulated, then further action may be taken.

In some embodiments, remedial action may also include directly orindirectly impeding water flow to some or all of the distributed waterinfrastructure. For example, a notification may be sent to a valve thatcauses the valve to restrict or completely halt water flow to some orall of the distributed water infrastructure. Alternatively, anotification may include a message to an individual of a potential leak,and may provide the individual with an option to intervene and shut offone or more valves. In another embodiment, if a notification is providedto a valve to halt water flow, a further notification may be provide toan individual to give the individual the ability to override the stop ofwater flow. In some embodiments, written notifications may be provided,for example, in the form of SMS messages, emails, social media messages,pop-ups, or through a dedicated application.

In accordance with the present disclosure, a remedial action may beinitiated, if at least one water profile does not substantiallycorrespond to a normal water event profile. In some embodiments, acurrent water event profile, which may be sensed in some distributedwater infrastructure, may be compared to a normal event profile usingmathematical operations that output a quantitative measure of similarityor dissimilarity between the two profiles. The current event profile maynot substantially correspond to the normal event profile if the measureof similarity or dissimilarity lies beyond the acceptable limits ofcorrespondence that may be defined for the normal event profile. Incertain embodiments, the acceptable limits of correspondence may beexpressed by a standard deviation or variance or any other quantitativemeasure of spread defined over the numerical representation of thenormal water event profile. The quantitative measure of dissimilaritymay be sufficient to identify an event of interest with a 75% confidenceinterval. The quantitative measure of dissimilarity may be sufficient toidentify an event of interest with an 85% confidence interval. Thequantitative measure of dissimilarity may be sufficient to identify anevent of interest with a 95% confidence interval.

In some embodiments, the system may include a transmitter wherein aremedial action may include sending, via the transmitter, a notificationto an administrator. An administrator of the abnormal consumptiondetection system that may be associated with a distributed waterinfrastructure may be an individual that has been designated responsiblefor monitoring and managing the system. This individual may also havebeen given authorization to access the system directly and interact withit through remote communication. In other embodiments, it is envisionedthat the individual may have a range of different access andresponsibilities. The administrator may be an individual who receivesall notifications from the system and may be responsible for respondingappropriately in every eventuality. In other embodiments, theadministrator may be a homeowner that receives a notification, andinstructs a third-party to respond appropriately in every eventuality.

In some embodiments, a system for detecting abnormal water consumptionmay send a notification, and the sending of the notification may occurthrough remote communication. The term remote communication includes anysystem that detects abnormal consumption and can notify theadministrator that abnormal consumption has been detected. In someaspects, sending a notification by remote communication may involvesending a message through a communication network to at least one remotecomputing device. The remote communication device may be accessed by anadministrator. The communication network may be a cellular, or a wiredor wireless network. The message may be conveyed through an SMS, ane-mail, or an indication on a website, or through a notification on amobile application, and the computing device may be a desktop computer,a laptop computer, or any mobile computer.

In some embodiments, at the time of classification, the normal waterevent profiles are not associated with a particular water appliance inthe distributed water system. In such embodiments, a normal water usagefor a distributed water infrastructure may include a plurality ofunassigned normal water profiles.

In some embodiments, the system for detecting abnormal water consumptionmay include at least one processor that is configured to enableassociation between a water event and an appliance in the distributedwater system. The system for detecting abnormal water consumption mayinclude at least one processor that is configured to enable associationbetween each time-based water event profile and each normal eventprofile and a specific appliance in the distributed water system. Insome embodiments, each time-based water event profile and each normalevent profile may be associated with a group of appliances in thedistributed water system. The at least one processor may be configuredto enable identification of a specific appliance based on at least oneparameter selected from an average flow rate, an initial flow rate, atotal volume associated with a current water event profile, a noise insignals indicative of water usage, and a change in the rate of waterusage.

It is contemplated that a water appliance may be any water-consumingdevice that may be physically connected to some distributed waterinfrastructure. In some embodiments, a water appliance consumes water.By way of example, a specific appliance may be a mechanical water outletsuch as a tap, sink, valve, or shower head. Other examples may includemore complex mechanical devices such as a toilet, or anelectro-mechanical device such as a dishwasher, washing machine, waterfiltration system, irrigation system, air-conditioning system, or anyother automatic or semi-automatic water consumer. A group of appliancesmay be a row of identical toilets in a bathroom.

In some embodiments, at least one processor may be configured to enableassociation between stored, and new, water event profiles to a knownappliance connected to the distributed water infrastructure. Associationmay be carried out automatically by the processor using prior knowledgeabout the water event profiles of specific appliances. Association maybe carried out semi-automatically whereby the processor uses priorknowledge of water event profiles to suggest the most likelyassociation, which an individual may confirm. Association may be carriedout manually whereby an individual associates the water event profileswith known appliances connected to the water system and submits thisassociation to the processor.

In some embodiments, a normal water event may be determined tosubstantially correspond with a known water event profile for a specificwater appliances, or group of water appliances, in the distributed watersystem. In other embodiments, it may be not necessary for a water eventto substantially correspond with a normal water event that may beassociated with a specific water appliance, such as when a specificappliance malfunctions a minimal correspondence may be sufficient tomatch a specific water appliance with a current water event profile. Inadditional embodiments, the water event may not be associated with aspecific water appliance at the time of classification, but may beassociated with a specific water appliance at a later time. The time ofclassification may be the time when a current water event profile isclassified either as a normal event or as an abnormal event.

In some embodiments, the at least one processor may be configured tocompare water events, which may include pattern recognition. Patternrecognition describes a process of grouping any number of events intogroups that share similar characteristics. In some embodiments, patternrecognition describes a process of comparing a new signal, which mayoriginate from a source and that may have been sensed by a sensor, withpreviously sensed typical signals originating from the same source inorder to determine if the new signal may be similar to one of thetypical signals and therefore can be classified as a recognized pattern.In some embodiments, patterns may be learned by manual identification orthrough computation using any machine learning technique whethersupervised, unsupervised, or semi-supervised, and recognition may beachieved by comparing new signals with learned signals using any measureof similarity or dissimilarity calculated in the feature space of thesignals where the feature space describes the quantitativerepresentation of the signals, obtained through a mathematicaltransformation of the original signal data.

In some embodiments, at least one processor may be configured to receivefrom an end user an indication of a specific appliance in use, and tostore in an associated manner, the specific appliance with a water eventprofile associated with the specific appliance. The at least oneprocessor may be configured to identify a water user associated with thewater event profile. Specific appliances may have a range of modes ofoperation that may vary for specific individuals. For example, anindividual may take a shower at a certain time of day, for a certainduration, and may use a specific shower in a certain location in thedistributed water infrastructure. The at least one processor may beconfigured to compare normal water event profiles to the current waterevent profile and associate the water usage with a particular user basedon a characteristic associated with a user. For example, acharacteristic associated with a user may be a period of time where auser is the only user using the distributed water infrastructure. Insome embodiments, a characteristic may be a duration that a water eventprofile may be used or a sequence that a group of devices are usedwithin a period of time. For example, an individual may be identified bya characteristic time between a toilet and sink being used, or theduration that a sink is used. In such embodiments, the processor may notbe configured to associate water event profiles with a specificappliance, such that use of the toilet and sink are associated withwater event profiles that are unique but not assigned to specificdevices. The at least one processor may be configured to compare normalwater event profiles to the current water event profile, identify aspecific appliance that may be used, and associate the water usage witha particular user.

In some embodiments, the at least one processor may be configured todetermine operation of the specific water appliance when the currentwater event profile deviates from the normal event profile by less thana predetermined amount. The at least one processor may be configured toidentify a partially malfunctioning appliance. The at least oneprocessor may be configured to associate a current water event profilewith a normal water event profile if the match is within a predeterminedamount or percentage.

In some embodiments, the at least one processor may be configured todetermine that the specific appliance may be in use before use of thespecific appliance is terminated. For example, the at least oneprocessor may be configured to identify the use of a shower by comparinga current water event profile with a stored shower normal water eventprofile, which may be based on an initial flow rate and average flowrate, such that after the shower is initiated the at least one processormay identify the appliance in use before the shower completes. The useof a washing machine may be identified after the end of a first cycle,such that the subsequent cycles are associated with the washing machine.

The at least one processor may be configured to determine from thecurrent water event profile a specific appliance that may be leaking,wherein the remedial action may include providing information to an enduser identifying the specific appliance. The at least one processor maybe further configured to provide to the end user information about acharacterization of the leaking of water. A characterization of theleaking of water may be any information regarding the appliance and/orthe leak. The information may be stored in association with the waterevent profile for the specific application. The information may beidentified from the at least one sensor contemporaneously with adetection of a leak. For example, the characterization of the leaking ofwater may be the flow rate of the leak, a stored location of anappliance that may be leaking, a total volume of water that has leaked,and an identification of the last appliance that was in use.

In some embodiments, the at least one processor may be configured toinitiate the remedial action when a duration of use of a specificappliance exceeds a duration of an associated normal water eventprofile. The at least one processor may be configured to determine thatthe specific appliance may be in use before use of the specificappliance is terminated, such that a remedial action can be initiated ifa usage exceeds a predetermined range or learned range of typical waterusage. In some embodiments, each normal water event profile may beassigned, by an administrator, a duration of use. The at least oneprocessor may be configured to determine a range of duration of use of aspecific appliance, by identifying a specific appliance, tracking theduration of water consumption each time the specific appliance was inuse, and determining a representative range of durations.

A distributed water infrastructure may experience abnormal water eventsthat may fall within a set of categories, such as an irrigation leak, adrip leak, and a pipe burst. Certain abnormal water events may havedefining characteristics that may be used as the basis for constructingabnormal water event profiles. These water event profiles may be storedin memory, such that when a current water event profile does not match anormal water event profile, the current water event profile may bematched versus stored abnormal water event profiles. The at least oneprocessor may be configured to compare the at least one current waterevent profile with abnormal water event profiles stored in memory and toinitiate remedial action when a substantial match is determined.

A distributed water infrastructure may experience abnormal water eventsthat are more likely to cause a significant amount of damage. Forexample, a high flow leak on an upper flow may be more likely to causedamage than a low flow leak outside. The at least one processor may beconfigured to distinguish between abnormal operation of appliancesunlikely to cause damage and abnormal operation of appliances likely tocause damage, wherein the remedial action may include closing a valvewhen abnormal operation likely to cause damage is detected. In someembodiments, each time-based water event profile and each normal eventprofile may be associated with a specific damage indicator. In certainembodiments, an end user may indicate certain specific appliances thatare considered high risks for leaks, and the system may be configured toidentify when a specific appliance is in use.

FIG. 2a illustrates an exemplary system 200 for detecting theconsumption of liquids. The components of system 200 discussed hereinare intended to be illustrative. In some embodiments, system 200 may beimplemented with one or more additional components not described, and/orwithout one or more of the operations discussed. Additionally, theconfiguration of the elements in which the components of system 200 areillustrated in FIG. 2a , and FIG. 2b , and described herein is notintended to be limiting.

Exemplary system 200 may be configured to carry out a procedure ofgathering measurements of liquid consumption according to aspects of thepresent disclosure. As shown in FIG. 2a , one or more sensors may beprovided in the system. In some embodiments, sensors may comprise anysensor that measures the consumption of water, including thenon-limiting examples of a flow sensor, a sonic water sensor, and apressure sensor. The system may include more than one sensor. Forexample, sensor 210 may be attached at some point in a distributed waterinfrastructure 100. In some embodiments, sensors may be configured togather information used to generate statistical and/or event-based dataregarding water consumption and relay the information to an end user280.

As shown in FIG. 2a , at least one processor may be provided in thesystem. In some embodiments, processor 220 may be configured as a partof a computer provided with a central processing unit (CPU) and memory230. In some embodiments, memory may include at least one of thenon-limiting examples of a random access memory (RAM), and a read-onlymemory (ROM). For example, processor 220 may read out a programcorresponding to detecting abnormal consumption in a distributed waterinfrastructure, load it into the RAM, and cause the CPU to perform aprocess corresponding to receiving, from sensor 210, signals indicativeof water usage in the distributed water infrastructure. The program maybe downloaded via a communication network or may be provided as storedin a storage medium in memory 230.

As shown in FIG. 2b , an exemplary system 201 may optionally includefurther components. It is explicitly considered that each additionalcomponent in FIG. 2b may be included, individually or in somecombination, in a system such as illustrated in FIG. 2a . In someembodiments, a system may include a valve 240. Valve 240 may beconfigured to halt the flow of water after receiving a signal from atleast one processor 220. The system may include an unmeasured flowreducer 250. The system may include a transmitter 260 and a wirelesscommunication device 261. The system may include a user interface 270.User interface 270 allows a user to interact with the system, and mayinclude a GUI, mechanical controls, electronic controls, electronicinterface, display, etc. Processor 220 may be configured to send analert to an end user 280.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, wherein the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits provided byevent-based leak detection systems and methods. In some embodiments, ameasurement of the number of liters consumed as a function of time maybe transformed into a water usage pattern that has a particularfingerprint or water usage pattern. A water usage pattern may bedetermined by any method consistent with identification herein, such asthe non-limiting examples of: event-based threshold method, guidedmachine learning, or automatic machine learning. Water usage patterndetermination may be assisted by a neural network, whereby a system mayprogressively improve performance to determine, identify, and comparewater usage patterns by considering examples. In some embodiments, aneural network may be used without task-specific programming. Forexample, a system may learn (without a specific program directed to thegranular task of comparing water usage patterns) to differentiatebetween water usage patterns, by considering exemplary water usagepatterns that are known to be different.

In various alternative methods, detecting the manner of consumption ofliquids may be implemented by alternative methods of receiving waterinformation, and employing event-based leak detection systems andmethods to provide granularity of water usage to an end user.

FIG. 3 illustrates an exemplary method 300 for detecting the consumptionof liquids. The operations of method 300 discussed here are intended tobe illustrative. In some embodiments, method 300 may be implemented withone or more additional operations not described, and/or without one ormore of the operations discussed. Additionally, the order in which theoperations of method 300 are illustrated in FIG. 3 and described hereinis not intended to be limiting.

In some embodiments, method 300 may be implemented in one or moreprocessing devices (e.g., a digital processor, an analog processor, adigital circuit designed to process information, an analog circuitdesigned to process information, a state machine, and/or any othermechanisms or types of processors for electronically processinginformation, including any processors described herein). The one or moreprocessing devices may include one or more devices executing some or allof the operations of method 300 in response to instructions storedelectronically on an electronic storage medium. The one or moreprocessing devices may include one or more devices configured throughhardware, firmware, and/or software to be specifically designed forexecution of one or more of the operations of method 300.

In some embodiments, at operation 310, at least one processor may beconfigured to receive from at least one sensor associated with thedistributed water infrastructure signals indicative of water usage inthe distributed water infrastructure. At operation 320, at least oneprocessor may be configured to aggregate groups of signals to constructa plurality of time-based water event profiles, each water event profilecontaining a distribution of water usage indicators over time. Atoperation 330, at least one processor may be configured to store asubset of the plurality of water event profiles in memory as normalwater event profiles. At operation 340, at least one processor may beconfigured to receive from the at least one sensor, signals indicativeof current water usage in the distributed water infrastructure. Atoperation 350, at least one processor may be configured to construct,from the signals indicative of current water usage, at least one currentwater event profile. At operation 360, at least one processor may beconfigured to compare the at least one current water event profile withnormal water event profiles stored in memory. At operation 370, at leastone processor may be configured to initiate remedial action if the atleast one current water event profile does not substantially correspondto normal water event profiles stored in memory.

An aspect of some embodiments may include a system for leak detection,water damage prevention, water savings, and the control of a waterconsumer's water system. The system may comprise a water flow metersensor and solenoid valve inside a standard water meter base. The systemmay be an install-and-forget system that connects a water system to theInternet. The system may enable alerting, monitoring, and control from amobile device or website, or from the system itself. The system maycomprise a manual override lever that enables a water consumer todeactivate the system's ability to shut down water flow. The overridemay still allow alerting a water consumer regarding abnormal waterconsumption, but the system might not shut down water flow. The systemmay also comprise a water inlet, which may connect the system to adistributed water infrastructure. The system may also comprise a systembase that may contain a metering unit and solenoid valve. The system mayalso comprise a status and control panel, which may display the systemstatus and enable a water user to permit water to flow through thedistributed water infrastructure if the system has been closed due to aremedial action.

An aspect of some embodiments may include a system that may include anartificial intelligent system (comprised of a learning mechanism andrelated algorithms) that continually monitors the water consumption of awater consumer's property. In some embodiments, a system may detectabnormal water flow and immediately alert a water consumer via textmessage to a mobile phone. The system may be connected to the Internetsuch that a website and/or application may provide detailed charts andgraphs indicating water consumption, including, for example, on anhourly basis. The system may be able to shut down water flow. The systemmay operate independently. Upon identifying excess water consumption, ineither open or hidden areas, during day or night, inside or outside aproperty, the system may alert an end user via text message to a mobiledevice.

According to user preferences, the system may either shut down the mainwater valve automatically or allow a water consumer to shut down thewater manually from a mobile device. The system may also enable an enduser to remotely override the shutdown from a mobile device. In someembodiments, a system may use its water flow meter sensor and itsartificial intelligence algorithms to learn the water consumptionpatterns on a property (e.g., in an adaptive mode). The system maycollect all the signatures of water usage patterns to be used as abaseline for detecting abnormal water consumption.

In some embodiments, for the first month after the system is installed,the system may monitor normal water consumption rates and patterns of aproperty in order to set up the baseline criteria to be used later asthe initial baseline for identifying abnormal water consumption. Duringthis month, the system might not shut down a property's water.

In some embodiments, an end user may deactivate the system's learningmechanisms and instead, use a personal website to enter the water usagethreshold values according to any schedule that one may want byspecifying various times of day, days of week and holidays, and thewater usage thresholds that will determine when the water may be shutdown.

In some embodiments, the system may include a home and away mode. Thesystem may enable remotely setting restrictive behavior when an end useris away from a property for more than 24 hours (such as during avacation).

In some embodiments, the system may enable an end user to define fixedthresholds and functionality per time of day and weekends. When thesystem detects moderate or major water consumption, it may immediatelyalert a water consumer via text message, mobile app, and website. Awater consumer may have the option to remotely override its decision toshut the water from their mobile app, website, or using their faucet. Ifa water consumer does not override the system's decision, then thesystem may automatically shut down the water flow. The system may enablea water user to reopen a water value remotely.

In some embodiments, if the system continues to detect moderate or majorabnormal water consumption after an end user has overridden the system'sautomatic shutting down of water, the system may send another alertafter 30 minutes or a determined time period, but it will not shut downthe water again.

In some embodiments, the systems and methods according to the presentdisclosure may categorize the severity of abnormal water events. Thesystems and methods may take different actions depending on thecategory. In some embodiments the system may categorize abnormal waterflow rates into three categories: minor, moderate, and major.

Minor abnormal water consumption may be equivalent to a tiny leak orwater dripping from a faucet. Notably, minor leaks can cause majordamage over time in the form of mold and building infrastructure damage.In some embodiments, a system, upon detecting minor abnormal waterconsumption, may send a message to a mobile device notifying about theabnormal water consumption. If the water consumption continues, thenanother message may be sent after a day, after a week, and after amonth. In some embodiments, no additional text messages might be sent toa mobile device after that.

In some embodiments, after a minor alert is sent, the system may ignoreall additional minor abnormal water consumption of the same magnitudeuntil after the current problem is resolved. This may mean, for example,that the minor water leak must be fixed before the system can detectadditional minor water leaks of the same magnitude. However, if a largerwater consumption abnormality is detected, the system may alert an enduser.

Moderate abnormal water consumption may be equivalent to a flow from aslightly open faucet. The difference between moderate and major abnormalwater consumption may depend on the flow rate. The larger the abnormalwater consumption, the quicker the system's reaction time may be to shutdown the water flow via a valve and sending notifications andre-notifications. Some abnormal water consumption may not fall into thiscategory. In some embodiments, if there is a constant flow for a periodof time at some rate, the constant flow may be categorized as abnormalwater flow.

In some embodiments, a system may be configured to send an alert to adevice, website and mobile application that the system has shut down thewater, or may shut down the water. The system may be configured toprovide a chance to override a shutdown action.

Major abnormal water consumption event may be equivalent to the flowfrom a completely open faucet or more serious event. According topreferences, a system may automatically and immediately shut off waterin order to prevent major damage, while providing an end user with avariety of remote options for overriding the system's decision to shutdown the water. The system may be configured to provide a chance tooverride its decision to shut down the water from a mobile device.

In some embodiments, a system may enable a water consumer to remotelymonitor the ongoing consumption of water (monthly, weekly, daily andhourly), to control the water system and to see water system alerts. Adevice may be installed on a property in order to analyze ongoing waterconsumption and to produce routine consumption data. Consumption datamay be displayed hourly, daily (e.g., last 7 days of consumption),weekly, and monthly. In some embodiments, a mobile app may enable awater consumer to get water system alerts directly from a mobile device,to remotely control a water system, and to monitor ongoing consumptionof water, on a monthly, weekly, daily, and hourly basis.

Exemplary Embodiments of Remote Valve Reopening Following AbnormalConsumption

The present application provides for remote valve reopening following apotential detected leak. A benefit of some embodiments of the presentdisclosure may be systems and methods may utilize an integrated leakdetection system with an application that permits remote valve reopeningvia a remote communication device.

An aspect of some embodiments may include an integrated abnormalconsumption detection system for a distributed water infrastructure.Such a system may include an electronically controllable valve. Anelectronically controllable valve may be an electromechanical deviceused to control fluid flow by varying the size of the flow passage asdirected by a signal from a controller. The flow passage may be fullyclosed. Automatic control valves may be open or closed by sending anelectrical signal from a controller to a solenoid that causes a valve toopen or close.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may include a communicationtransmitter. The communication transmitter may be a remote communicationtransmitter. A communication transmitter may be any electroniccommunication device used to transmit information between at least twodevices. For example remote communication transmitter may transmitinformation via a wire or remote communication network.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may include a communicationreceiver. The communication receiver may be a remote communicationreceiver. A communication receiver may be any electronic communicationdevice used to receive information between at least two devices. In someembodiments, a remote communication receiver may receive information viaa wire or remote communication network.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may include at least oneconsumption sensor for measuring water flow information associated withthe distributed water infrastructure. A sensor may be any of the sensorsdescribed herein. The sensor may be configured to measure any physicalproperty that indicates the quantity of water per unit of time thatflows through a distributed water infrastructure. The water flowinformation may be measured in liters per hour or in gallons per hour.In some embodiments, flow information may include at least one of flowrate and flow volume. Flow information may be gathered from a signalthat is sent every time the sensor measures a given amount of volume haspassed the sensor.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may include at least oneprocessor configured to determine from the water flow information,obtained from the sensor, a potential abnormal consumption associatedwith the distributed water infrastructure. Abnormal consumption may bedefined by a mathematical function that characterizes a known,undesirable consumption profile, which may then be compared with asensed consumption profile in order to identify an abnormality. Theabnormal water consumption may be characterized by a sensed waterconsumption profile. Abnormal water consumption may refer to any waterconsumption profile sensed in a distributed water infrastructure thatdeviates significantly from one or more pre-learned water consumptionprofiles that characterize normal consumption in that water system. Insome embodiments, an abnormal water consumption profile should differsignificantly from the known water consumption profiles. The significantdeviation may be measured quantitatively by comparing the sensed waterconsumption profile with each of the pre-learned consumption profilesusing any suitable distance measure of similarity or dissimilarity. Thedeviation of the sensed consumption profile from a pre-learnedconsumption profile may be considered significant when the distance ofthe sensed consumption profile is beyond the acceptable distance limitsdefined for the pre-learned consumption profile.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may automatically close a valve,without human intervention when a potential abnormal consumption isdetermined. The system may transmit, via the remote communicationtransmitter to a remote administrator, information about the potentialabnormal consumption to enable an administrator to decide based on thetransmitted information whether to reopen the valve.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may wait for confirmation from anadministrator before closing a valve. The integrated abnormalconsumption detection system for a distributed water infrastructure mayreceive from the administrator via the remote communication receiver acontrol signal to close the valve.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may be configured toautomatically reopen the valve after a period of time. The at least oneprocessor may be configured to reopen the valve if information from theat least one sensor determines an abatement of the potentially abnormalwater condition.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may send an alert that may assistthe end user in determining whether to open or re-open the valve. Thealert information may include at least one of flow rate, flow volume,and an indication of a water-consuming appliance likely to bemalfunctioning.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may receive from an administratorvia a remote communication receiver a control signal to reopen thevalve. The administrator may choose to re-open the valve despiteinformation about the potential abnormal consumption, and the valvewould be reopened.

A control signal may refer to a pulse of electricity, or any othertransmitted signal, that represents a control command generated by acontroller. Such a pulse may travel over a network or a computer channelusing wired or wireless communication. At least one of the remotecommunication transmitter and the remote communication receiver may bewireless.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may include an integrated remotecommunication transmitter and remote communication receiver. The twocommunications units may be combined in one electronic unit that unitesboth the transmitting and receiving function. In another embodiment, theremote communication transmitter and remote communication receiver maynot be integrated. At least one of the remote communication transmitterand the remote communication receiver may be wireless. The termwireless, or wireless communication, refers generally to the transfer ofinformation between two or more points that are not connected by anelectrical conductor. In wireless communication, information may betransferred over both long and short distances. Examples of wirelesscommunication may include, but are not limited to, GPS units, radioreceivers, satellite television, LTE, Wi-Fi, and Bluetooth.

In some embodiments, the at least one consumption sensor may include atleast two sensors, wherein the at least one processor may be furtherconfigured to receive water flow information from at least two sensors.A sensor according to the present disclosure may include a sensor hub. Asensor hub may receive information from at least one sensor. The sensorhub may be a device that comprises a microcontroller unit andinterfaces, and may integrate data from different sensors and processthe data. Examples of the different sensor data types that may beincorporated into a sensor hub include flow rate, flow pressure, andtemperature. Further, a sensor may measure other water qualityproperties such as pH, conductivity, fluorine concentration, and thepresence of a biofilm.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may include a valve, wherein thevalve is closed or opened based on a measurement of or from a sensor. Ameasurement from a sensor may be any electrical signal generated by asensor and delivered to a sensor hub or controller. Such electricalsignals may be proportional to physical properties, such as, but notlimited to, pressure, water flow rate, acceleration, and temperature.

In some embodiments, an integrated abnormal consumption detection systemfor a distributed water infrastructure may include at least oneprocessor configured to determine from the water flow information anappliance likely associated with the abnormal consumption and toidentify a subsystem valve associated with the appliance, whereinautomatically closing the valve may include closing the subsystem valveto isolate the appliance from at least a portion of the distributedwater infrastructure.

The system may include a transceiver that integrates the remotecommunication transmitter and the remote communication receiver. Thesystem may include at least one processor configured to ignore thepotential abnormal consumption, store in memory the water flowinformation associated with the potential abnormal consumption, and takeno remedial action when the potential abnormal consumption is below ashut-off threshold.

An aspect of some embodiments may include an abnormal water consumptiondetection system for a distributed water infrastructure. In accordancewith the present disclosure, a system for detecting flow of a fluid mayinclude at least one processor. The at least one processor may includeany physical device having an electric circuit that performs a logicoperation on input or inputs. For example, a processor may include oneor more integrated circuits, microchips, microcontrollers,microprocessors, all or part of a central processing unit (CPU),graphics processing unit (GPU), digital signal processor (DSP),field-programmable gate array (FPGA), or other circuits suitable forexecuting instructions or performing logic operations. The instructionsexecuted by a processor may, for example, be pre-loaded into a memoryintegrated with or embedded into the processor or may be stored in aseparate memory.

More than one processor may be used for any function. Each processor mayhave a similar construction or the processors may be of differingconstructions that are electrically connected or disconnected from eachother. For example, the processors may be separate circuits orintegrated in a single circuit. When more than one processor is used,the processors may be configured to operate independently orcollaboratively. The processors may be coupled electrically,magnetically, optically, acoustically, mechanically, or by other meansthat permit them to interact.

In one embodiment, a processor may be a data processor, a personalcomputer, or a mainframe for performing various functions andoperations. The system for detecting abnormal consumption of water in adistributed water infrastructure may be implemented, for example, by ageneral purpose computer or a data processor selectively activated orreconfigured by a stored computer program, or may be a speciallyconstructed computing platform for carrying out the features andoperations described herein. Moreover, the system for detecting abnormalconsumption of water in a distributed water infrastructure may beimplemented or provided with a wide variety of components or systems,including one or more of the following: central processing units,co-processors, memories, registers, or other data processing devices andsubsystems.

In some embodiments, an integrated abnormal consumption detection systemmay include at least one processor configured to receive, from at leastone sensor associated with the distributed water infrastructure, waterusage information for the distributed water infrastructure. The systemmay include at least one processor configured to determine, from thewater usage information, an event likely to be an abnormal consumptionwithin the distributed water infrastructure. The system may include atleast one processor configured to send, via a transmitter, an alertmessage to an administrator notifying the administrator of the likelyabnormal consumption, and providing to the administrator data associatedwith the likely abnormal consumption. The system may include at leastone processor configured to receive from the administrator via areceiver a command, the command being chosen from a group consisting ofan ignore command and a remedial action command. The system may includeat least one processor configured to permit water to flow through avalve after the ignore command is received.

In some embodiments, at least one processor may be configured to close avalve in response to receipt of the remedial action command. At leastone processor may be configured to store a profile of the likelyabnormal consumption associated with the ignore command, and to avoidsending a subsequent alert message to the administrator at a later timewhen the profile may be detected again. The data associated with thelikely abnormal consumption provided to the administrator may include atleast one of flow rate, flow volume, and an indication of an identity ofan appliance likely to be malfunctioning. Data provided to theadministrator may include location information of the appliance likelyto be malfunctioning.

In some embodiments, the at least one processor may be configured tostore in memory appliance information including at least one of locationinformation and identity information for at least one water-consumingappliance in the distributed water infrastructure, associate the likelyabnormal event with appliance information, and send to the administratorvia the transmitter the appliance information when a likely abnormalevent is determined. The at least one processor may be configured topredict identities of a plurality of water appliances in the distributedwater infrastructure based on the water usage information.

In some embodiments, the processor may be configured to provide, via thetransmitter, updated data to the administrator following the message inorder to enable the administrator to assess ongoing severity. The atleast one processor may be configured to determine a sub-system valvethat isolates at least one appliance likely associated with an abnormalwater event from other portions of the distributed water infrastructure,and to close the sub-system valve in response to the remedial actioncommand. The at least one processor may be configured to close the valveif a command is not received from the administrator within apredetermined time period following message transmission to theadministrator.

An aspect of some embodiments may include an abnormal consumptiondetection system for a distributed water infrastructure. In someembodiments, the system may comprise at least one processor configuredto determine from water flow information obtained from at least onesensor a potential abnormal consumption associated with the distributedwater infrastructure. The at least one processor may be configured todetermine, from the water flow information, an identity of awater-consuming appliance associated with the potential abnormalconsumption. The at least one processor may be configured toautomatically close a valve without human intervention, which shuts offwater flow to the determined water-consuming appliance.

In some embodiments, at least one processor may be further configured totransmit, via a remote communication transmitter to a remoteadministrator, information about the potential abnormal consumption toenable the remote administrator to decide based on the transmittedinformation whether to reopen the valve. The at least one processor maybe further configured to receive from the remote administrator via aremote communication receiver a control signal to reopen the valve,despite the information about the potential abnormal consumption, and toreopen the valve in response to the control signal.

FIG. 4a illustrates an exemplary system 400 for remote valve reopeningand/or automatic valve closure after the detection of abnormalconsumption. The components of system 400 discussed herein are intendedto be illustrative. In some embodiments, system 400 may be implementedwith one or more additional components not described, and/or without oneor more of the operations discussed. Additionally, the configuration ofthe elements in which the components of system 400 are illustrated inFIGS. 4a and 4b , and described herein, is not intended to be limiting.

Exemplary system 400 may be configured to carry out a procedure ofremote valve reopening following potential detected abnormal consumptionaccording to aspects of the present disclosure. As shown in FIG. 4a ,one or more consumption sensors 410 may be provided in the system. Insome embodiments, processor 420 may be configured as a part of acomputer provided with a central processing unit (CPU). The system mayinclude a controllable valve 440. Valve 440 may be configured to haltthe flow of water after receiving a signal from at least one processor420. The system may include a communication transmitter 460 and acommunication receiver 462. A remote administrator 482 may send and/orreceive information to and from communication transmitter 460 andcommunication receiver 462.

As shown in FIG. 4b , an exemplary system 401 may include othercomponents. It is explicitly considered that each component in FIG. 4bmay be included, individually or in some combination, in a system suchas illustrated in FIG. 4a . In some embodiments, a system may includewireless communication. The system may include communication transceiver463, which may combine communication transmitter 460 and communicationreceiver 462. Transceiver 463, transmitter 460, and receiver 462 may bewireless or wired. The system may include subsystem valve 441, which maybe connected to another location in the distributed water infrastructure100. The system may include exterior valve handle 442, which may allowfor manual close of a valve 440. In some embodiments, a system mayinclude sensor hub 411, which may include multiple sensors in additionto a consumption sensor 410.

FIG. 5a illustrates an exemplary method 500 for remote valve reopeningand/or automatic valve closure after the detection of abnormalconsumption. The operations of method 500 discussed herein are intendedto be illustrative. In some embodiments, method 500 may be implementedwith one or more additional operations not described, and/or without oneor more of the operations discussed. Additionally, the order in whichthe operations of method 500 are illustrated in FIG. 5a and describedherein is not intended to be limiting.

In some embodiments, method 500 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all of the operations of method 500 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more of the operations ofmethod 500.

In some embodiments, at operation 510, at least one processor may beconfigured to determine from the water flow information obtained fromthe at least one consumption sensor a potential abnormal consumptionassociated with the distributed water infrastructure. At operation 520,at least one processor may be configured to automatically close a valve,without human intervention, when the potential abnormal consumption isdetermined. At operation 530, at least one processor may be configuredto transmit, via the remote communication transmitter to a remoteadministrator, alert information about the potential abnormalconsumption to enable an administrator to decide based on thetransmitted information whether to reopen the valve. At operation 540,at least one processor may be configured to receive from theadministrator via the remote communication receiver a control signal toreopen the valve, despite the information about the potential abnormalconsumption. At operation 550, at least one processor may be configuredto reopen the valve.

FIG. 5b illustrates an exemplary method 501 for remote valve reopeningand/or automatic valve closure after the detection of abnormalconsumption. The operations of method 500 discussed herein are intendedto be illustrative. In some embodiments, method 501 may be implementedwith one or more additional operations not described, and/or without oneor more of the operations discussed. Additionally, the order in whichthe operations of method 501 are illustrated in FIG. 5b and describedherein is not intended to be limiting.

In some embodiments, method 501 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all of the operations of method 501 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more of the operations ofmethod 501.

In some embodiments, at operation 560, at least one processor may beconfigured to determine from the water flow information obtained fromthe at least one consumption sensor a potential abnormal consumptionassociated with the distributed water infrastructure. At operation 562,at least one processor may be configured to issue a warning to a user.

At operation 564, at least one processor may be configured to identifyif the user has ignored the warning of an abnormal consumption. In someembodiments, a warning of an abnormal consumption may be in the form ofat least one of a text message on a phone, a notification on a phone,and a notification on a web-based GUI. A user may ignore the warning ofan abnormal consumption by taking no action, and a user may ignore thewarning by dismissing a notification on their phone.

In some embodiments, where the user ignores a warning of an abnormalconsumption, abnormal consumption may stop or abate. Accordingly, atoperation 566, at least one processor may be configured to receive acommand from a user to either close a valve or ignore the warning. Ifthe user sends a command action to ignore a warning, then at operation568 at least one processor may be configured to cancel the warning.Canceling a warning may include configuring a setting to indicate thatfuture abnormal events matching the abnormal consumption will beignored. In addition, or in an alternative, cancellation of a warningmay include configuring a setting that indicates that a future waterevent matching the ignored abnormal consumption will be considered atype of normal water consumption. If, instead of sending a command tothe system to ignoring a warning, the user sends a command action toclose the valve, at operation 570, at least one processor may beconfigured to close the valve. At operation 572, at least one processormay be configured to receive a signal to reopen the valve, and atoperation 574, at least one processor may be configured to reopen aclosed valve.

In some embodiments, where the user ignores a warning of an abnormalconsumption, abnormal consumption may continue. In the absence of aresponse from a user, at operation 570, at least one processor may beconfigured to close a valve. At operation 572, at least one processormay be configured to receive a signal to reopen the valve, and atoperation 574, at least one processor may be configured to reopen aclosed valve. A signal to reopen the valve may be sent by a user, butmay also be sent automatically at a specified time. For example, anabnormal event that occurs overnight may trigger the automatic closingof a water valve for a distributed water infrastructure, but in orderfor water to be available the next morning, the valve may beautomatically opened.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, wherein the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time, e.g., through abatch process or delayed process. The processing operations may also beprovided by distributed parallel or cloud computing infrastructures withdata and results transported to the cloud or parallel processor usingwireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits provided byevent-based leak detection systems and methods. In some embodiments, ameasurement of the number of liters consumed as a function of time maybe transformed into a water usage pattern that has a particularfingerprint or water usage pattern. A water usage pattern may bedetermined by any method consistent with identification herein, such asthe non-limiting examples of: event-based threshold method, guidedmachine learning, or automatic machine learning. Water usage patterndetermination may be assisted by a neural network, whereby a system mayprogressively improve performance to determine, identify, and comparewater usage patterns by considering examples. In some embodiments, aneural network may be used without task-specific programming.

In various alternative methods, remote valve reopening and/or automaticvalve closure after the detection of abnormal consumption may beimplemented by alternative methods of receiving water information, andemploying event-based leak detection systems and methods to providegranularity of water usage to an end user.

Exemplary Embodiments of Preventing Frozen Pipe Breaks

The present application provides for systems for preventing frozen pipebreaks. One potential benefit of systems that include a sensor capableof detecting when a pipe is about to freeze, and then release a valve,is to prevent damage caused by frozen pipes and resulting leaks. Asystem consistent with the present disclosure may be configured toautomatically open a release valve to initiate mitigating flow throughan at-risk pipe. A transmitter may remotely send a notification to anadministrator with the ability to initiate this or other remedialactions.

An aspect of some embodiments may include a system for mitigating frozenpipe bursts. The system may comprise at least one processor. The atleast one processor may be configured to receive from a sensorassociated with a pipe in a distributed water infrastructure at leastone signal indicative of the pipe being in a near-freezing pipecondition. The at least one processor may be configured to analyze theat least one signal to determine whether remedial action may bewarranted. The at least one processor may be configured to generate acontrol signal for causing a remedial action associated with thenear-freezing pipe. The at least one processor may be configured tocause the control signal to be transmitted to thereby commence theremedial action in order to reduce a possibility of a bursting of thenear-freezing pipe.

In some embodiments, the control signal may include a command to open avalve associated with the freezing pipe. The valve may be a tricklevalve. The system may be configured to transmit leak warnings and thesystem may be further configured to avoid sending leak warningsassociated with flow through the trickle valve. The remedial action mayinclude sending, via a remote communication transmitter, a notificationto an administrator and opening a trickle valve.

In some embodiments, the at least one processor may be configured toreceive from the administrator a trickle valve open command, wherein theprocessor may be further configured to transmit the control signal tothe trickle valve in response to the trickle valve open command. The atleast one sensor may include a temperature sensor. The at least oneprocessor may be configured to receive a plurality of signals from aplurality of sensors across the distributed water system. Each of theplurality of sensors may have an address associated with a location inthe distributed water system. The at least one processor may beconfigured to open at least one of a plurality of trickle valves in alocation proximate to a sensor from which a near-freezing conditionsignal emanates.

In some embodiments, the at least one processor may be configured tomaintain a unique identifier address for each of the plurality ofsensors and the plurality of trickle valves, and to associate at leastone sensor unique identifier address with at least one trickle valveidentifier address. When a remedial instruction is received, the atleast one processor may enable opening of a trickle valve associatedwith a corresponding sensor that prompted the remedial instruction.

Exemplary Embodiments of Abnormal Consumption Detection During NormalWater Usage

The present application provides for leak detection during normal waterusage. A potential benefit of some embodiments may include the abilityto detect abnormal consumption, even during times of normal water usage.In some embodiments, this may be done by determining a baseline ofexisting usage, and ascertaining a non-expected deviation from thebaseline. In addition or in the alternative, systems and methods may beable to identify the use of water at a granular level, such that normalwater usage may be categorized into discrete events, and the addition ofa new unrecognized event may indicate a leak.

An aspect of some embodiments may include a system for detectingabnormal consumption in a distributed water infrastructure while waterusage occurs in the infrastructure. The system may comprise at least oneprocessor. In some embodiments, the at least one processor may beconfigured to receive from at least one sensor associated with thedistributed water infrastructure indications of regular water usage. Anindication of regular water usage may be a signal indicating waterconsumption originating from at least one correctly functioningwater-consuming appliance that may be connected to a distributed waterinfrastructure, which may be faultless.

A water-consuming appliance may be any appliance that consumes waterwhether mechanical such as a faucet or a toilet, or electro-mechanicalsuch as a washing machine or dish-washer for which the term “correctlyfunctioning” implies that it is not damaged or malfunctioning in any waythat may impede or interfere with its normal water-consuming function. Afaultless distributed water infrastructure may be one that is notsubject to any blockages or leaks and for which all the water consumersconnected to it are working correctly.

Indications of regular water usage may be signals received from a sensorassociated with the distributed water infrastructure that are eachrepresented by some quantitative value equivalent to the time when thesignal was received, whether as a time stamp or a as relative timedifference, since the previous signal or as cumulative measure of timefrom a reference in time.

In some embodiments, the at least one processor may be configured todetermine from a plurality of indications received over a time period, aplurality of baseline water usage profiles. A baseline water usageprofile may be a normal water event profile that characterizes specificwater usage that may occur regularly or predictably in a distributedwater system and therefore represents a typical usage of water in thatwater system. Within a plurality of baseline profiles, each profile maycorrespond to a particular water consumer connected to the distributedwater infrastructure or a typical use of a particular water consumer. Aprofile may have several levels of specificity. For instance, onebaseline water usage profile may be associated with washing of hands ina faucet. Another level of baseline water usage profiles may beassociated with a particular user, who usually cooks and washes theirhands multiple times during cooking or uses a dishwasher after the meal.These baseline water event profiles may be learned during a learningperiod. These baseline profiles may also be informed by previouslyestablished water event profiles. A baseline water profile may be savedin the memory of at least one processor associated with the distributedwater system and, either individually or together with other baselinewater usage profiles, may provide a reference that characterizes thenormal water consumption in the distributed water system.

In some embodiments, the at least one processor may be configured toreceive from the at least one sensor a current water usage profile. Acurrent water usage profile may be an indication of the current waterconsumption. A current water usage profile may be a signal indicatingwater consumption originating from at least one correctly functioningwater-consuming appliance that may be connected to a distributed waterinfrastructure. In some embodiments, a distributed water infrastructuremay be faultless. A faultless distributed water infrastructure may beone that is not subject to any blockages or leaks, such that all thewater consumers and/or appliances connected to it are working asintended. A water consumer may be any appliance that consumes waterwhether mechanical such as a faucet or a toilet, or electro-mechanicalsuch as a washing machine or dish-washer. The term “correctlyfunctioning” implies that such a water consumer or appliance is notdamaged in a way that may impede or interfere with its water-consumingfunction.

Indications of regular water usage are gathered by signals received froma sensor associated with the distributed water infrastructure.Indications of water usage may be characterized by a quantitative valueequivalent to the time when the signal was received. The quantitativevalue may be a time stamp, a relative time difference since the previoussignal, or a cumulative measure of time from a reference in time.

In some embodiments, the at least one processor may be configured tocompare the current water usage profile with the plurality of baselinewater usage profiles. Where there are no faults in the water system, thecurrent water usage profile may find agreement between the current waterusage profile and at least some of the profiles in a plurality of storedbaseline water usage profiles.

In some embodiments, the at least one processor may be configured todetermine a likely abnormal water consumption based on the comparisonbetween the current water usage profile and the plurality of baselinewater usage profiles. An abnormal water consumption signal may be acurrent event profile that is not similar enough or too different to thebaseline water event profiles that have been constructed for adistributed water infrastructure and may be therefore consideredabnormal for that water infrastructure. The acceptable limits ofsimilarity or difference between a baseline profile and a current eventprofile may be defined by a quantitative range that deviates from eachbaseline profile. The quantitative range may be flexible for each waterconsumption profile. In some embodiments, if a water consumption profileconsumes a large amount of water, then the quantitative range may berelatively large compared to a smaller water consumption event. If thewater consumption profile includes many varying levels of waterconsumption, but shares other characteristics for a water consumer, thenthe quantitative range may be directed to characteristics other than theamount of water consumed. In some embodiments, the at least oneprocessor may be configured to generate an abnormal water consumptionsignal when likely abnormal water consumption is determined.

An aspect of the disclosure may be directed to a system for detectingabnormal consumption in a distributed water infrastructure while waterusage occurs in the infrastructure. The system may comprise at least oneprocessor configured to receive from at least one sensor associated withthe distributed water infrastructure indications of regular water usage,determine from a plurality of indications received over a time period aplurality of baseline water usage profiles, receive from the at leastone sensor a current water usage profile, compare the current waterusage profile with the plurality of baseline water usage profiles,determine a likely abnormal water consumption based on the comparisonbetween the current water usage profile and the plurality of baselinewater usage profiles, and generate an abnormal water consumption signalwhen likely abnormal water consumption is determined.

In some embodiments, the determined plurality of baseline water usageprofiles may include a plurality of profiles unique to appliances withinthe distributed water infrastructure. At least one processor may beconfigured to receive from an end user an indication of a specificappliance in use, and to store in an associated manner, the specificappliance with a baseline water usage profile associated with thespecific appliance. At least one processor may be configured todetermine specific appliances without input from an end user. Someappliances may be identifiable without input from an end user, due toidentifiable characteristics of the water consumption. By way ofnon-limiting examples, the identifiable water characteristics may be aninitial flow rate, a sustained flow rate, and a total volume of waterconsumed. For example, the use of a shower may be determined by a flowrate of 8 liters per minute, and a flow rate that lasts for 8 minutes.

In some embodiments, the distributed water infrastructure may include aplurality of water-consuming appliances, wherein each of a plurality ofbaseline water usage profiles may be associated with a differingspecific appliance within the distributed water infrastructure.Following an addition of a new water appliance to the distributed waterinfrastructure, the at least one processor may be configured to adjustat least some of the baseline water usage profiles associated with otherappliances in the distributed water infrastructure. In such an instance,the system will not initiate an unnecessary leak alert after theaddition of an appliance.

Profiles unique to appliances are signals or groups of signalsindicative of water consumption over time that have been identified asoriginating from an appliance connected to the distributed waterinfrastructure. In some embodiments, there may be only a singleappliance with the unique water consumption profile. In anotherembodiment, there may be several appliances, e.g. faucets, that share adistinctive water consumption profile. An appliance may be either amechanical appliance such as a toilet or a tap in a sink or in a shower,or an electro-mechanical device such as a dish-washer, washing machine,water-filtration system, or automatic irrigation system. Such profilesmay uniquely identify water consumption by a particular appliance.

In some embodiments, a quantitative comparison may occur between thecurrent water usage profile and at least one baseline profile. Thecurrent water usage profile may be the group of signals received by atleast one processor from at least one sensor associated with adistributed water infrastructure, which are produced by at least oneconsumer or appliance in the distributed water infrastructure. In someembodiments, when no water consumption is occurring the waterconsumption profile may be zero. The current water consumption profilemay include a signal or group of signals that at least one appliance iscurrently consuming water.

A quantitative comparison of the current water event profile with abaseline water event profile may be achieved by applying a suitablemathematical operation on the data of the two profiles, which calculatesa measure either of similarity or dissimilarity between them andexpresses this measure with a quantitative value. In some embodiments,quantitative comparison involves subtraction of one compared profileversus another compared profile, and the magnitude of the remainder maybe used to determine a match. Part of a profile may be compared withanother profile. As a non-limiting example, two handwashing water usagepatterns that last a different amount of time may be matched bycomparing the beginning of the water usage patterns.

A quantitative comparison of the current water event profile with abaseline water event profile may be achieved by applying a form ofsubtraction of the data or the pre-processed data of one of the profilesfrom the other, which produces a measure of dissimilarity between thetwo profiles expressed by a single quantity representing this deviation.In some embodiments, quantitative comparison involves subtracting aknown water consumption rate from the current water consumption rate,and concluding that the current water consumption profile matches aknown baseline water consumption profile, if the remainder aftersubtraction is substantially zero.

In some embodiments, the abnormal water consumption signal contains anindication of an appliance likely to be leaking. The abnormal waterconsumption signal may be accompanied by a device that is likely causingthe leak.

In some embodiments, an indication that an appliance may be leakingduring an abnormal consumption event may be determined by matching thecurrent water consumption profile to a unique appliance, but where themeasure of comparison of the abnormal consumption profile exceeds amaximal value for at least one of the profiles of unique appliances.This quantitative measure of comparison may constitute a combination ofsimilarity and dissimilarity measures applied to all or parts of theprofiles being compared. In some embodiments, a likely device to becausing the abnormal water consumption may be identified by the timethat the leak occurs. For example, if showers are usually taken at acertain time in the morning, and a leak occurs at that time, then anindication may be provided that suggests that the leak may be associatedwith the shower.

In some embodiments, an abnormal water consumption signal may beconfigured to trigger a remedial action for abating the abnormalconsumption, wherein the remedial action may include at least one ofsending an alert and automatically closing a valve. At least oneprocessor may be configured to detect changes in at least two baselinewater usage profiles within a predetermined period and generate a signalindicating a blockage in the distributed water infrastructure. The atleast one processor may be configured to detect a change in at least onecharacteristic of at least one baseline water usage profile. The atleast one characteristic may be selected from an initial rise in flowrate, an average sustained flow rate, a total amount of water consumed,a duration of the baseline water usage profile, and cycles of waterusage.

In some embodiments, at least one processor may be configured to comparethe current water usage profile against known abnormal water eventprofiles. The at least one processor may be configured to receive, froman end user, information on abnormal water event profiles. Comparing mayinclude a subtraction of the current water usage profile and at leastone baseline water usage profile to determine if a remainder matches apredetermined threshold for a leak.

In some embodiments, at least one processor may be configured todetermine a specific appliance associated with the abnormal waterconsumption by identifying a recently-used appliance. The at least oneprocessor may be configured to determine a specific appliance associatedwith the abnormal water consumption by determining whether a currentwater usage profile differs from a baseline water usage profile by morethan a threshold difference in similarity.

In some embodiments, at least one processor may be further configured tocompare the current water usage profile and a baseline water usageprofile by deconstructing each profiles into subcomponents and comparingsubcomponents. The at least one processor may be configured to determinea malfunction in a specific water appliance in the distributed waterinfrastructure by accessing memory storing a reference water usageprofile of the specific water appliance, comparing a current water usageprofile associated with the specific appliance with the reference waterusage profile, and determining an appliance malfunction based on atleast one difference identified in the comparing.

In some embodiments, at least one sensor may be a flow sensor with anunmeasured flow reducer. At least one sensor may be configured to detectflow at a rate of less than about 2 liters per hour.

FIG. 6 illustrates an exemplary method 600 for detecting abnormalconsumption in one portion of a distributed water infrastructure whilenormal water usage occurs in another portion of the distributed waterinfrastructure. The operations of method 600 discussed herein areintended to be merely illustrative. In some embodiments, method 600 maybe implemented with one or more additional operations not described,and/or without one or more of the operations discussed. Additionally,the order in which the operations of method 600 are illustrated in FIG.6 and described herein is not intended to be limiting.

In some embodiments, method 600 may be implemented in one or moreprocessing devices (e.g., a digital processor, an analog processor, adigital circuit designed to process information, an analog circuitdesigned to process information, a state machine, and/or othermechanisms for electronically processing information). The one or moreprocessing devices may include one or more devices executing some or allof the operations of method 600 in response to instructions storedelectronically on an electronic storage medium. The one or moreprocessing devices may include one or more devices configured throughhardware, firmware, and/or software to be specifically designed forexecution of one or more of the operations of method 600.

In some embodiments, at operation 610, at least one processor may beconfigured to receive from at least one sensor associated with thedistributed water infrastructure indications of regular water usage.While this operation may serve the purpose of gathering information forbaseline water usage, a large facility or an analogous waterdistribution infrastructure may share sufficient characteristics that abaseline water usage could be shared between at least two devices. Insome embodiments, this step may not be necessary and the system may notinclude configuring to receive from at least one sensor associated withthe distributed water infrastructure indications of regular water usage.At operation 620, at least one processor may be configured to determinefrom a plurality of indications received over a time period, a pluralityof baseline water usage profiles. At operation 630, at least oneprocessor may be configured to receive from the at least one sensor acurrent water usage profile.

At operation 640, at least one processor may be configured to comparethe current water usage profile with the plurality of baseline waterusage profiles. At operation 650, at least one processor may beconfigured to determine an abnormal water consumption based on thecomparison between the current water usage profile and the plurality ofbaseline water usage profiles. At operation 660, at least one processormay be configured to generate an abnormal water consumption signal whenabnormal water consumption is determined.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, wherein the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits provided byevent-based leak detection systems and methods. In some embodiments, ameasurement of the number of liters consumed as a function of time maybe transformed into a water usage pattern that has a particularfingerprint or water usage pattern. A water usage pattern may bedetermined by any method consistent with identification herein, such asthe non-limiting examples of: event-based threshold method, guidedmachine learning, or automatic machine learning. Water usage patterndetermination may be assisted by a neural network, whereby a system mayprogressively improve performance to determine, identify, and comparewater usage patterns by considering examples. In some embodiments, aneural network may be used without task-specific programming.

In various alternative methods, detecting abnormal consumption in oneportion of a distributed water infrastructure while normal water usageoccurs in another portion of the distributed water infrastructure may beimplemented by alternative methods of receiving water information, andemploying event-based leak detection systems and methods to providegranularity of water usage to an end user.

Exemplary Embodiments of Low Flow Abnormal Consumption Detection DuringPeriods of No Water Usage

The present application may provide for slow leak detection duringperiods of no water usage. A potential benefit of systems and methods ofthe present disclosure may include allowing the examination of liquidflow during periods when no water use is expected, such as on weekendsor at night. During such times, water usage, particularly low flow orlow volume usage, may be likely attributable to a leak. The ability todiscern flow during specific times, as opposed to general thresholdsover the course of a month, are valuable to determine low level leaks.

An aspect of some embodiments may include a system for detectingabnormal consumption in a distributed water infrastructure. In someembodiments, the distributed water infrastructure may include aplurality of water appliances. The system may include at least oneprocessor configured to receive from at least one sensor associated withthe distributed water infrastructure indications of regular water usage.At least one processor may be configured to determine, from theindications received over a time period, at least one recurring timeperiod of expected diminished water usage.

At least one processor may be configured to determine, for the at leastone recurring time period of expected diminished water usage, at leastone expected diminished water usage profile. In some embodiments, the atleast one processor may be configured to determine, from a plurality ofindications received over a time period, at least one expected waterusage profile. A time period may refer to a sufficient period of timefor the system to gather enough indications of water consumption inorder for it to determine typical water usage profiles for that waterinfrastructure. An expected water usage profile may refer to a pluralityof signals indicative of water usage in a distributed waterinfrastructure that originate from the usage of a particular waterconsumer, such as a water appliance, which may be connected to thatwater infrastructure. The system may operate for an extended period oftime to gather representative data from the different consumers that areconnected to the distributed water infrastructure. Additionally oralternatively, the system may operate for a relatively short amount oftime if the full range of different consumers occurs over a short periodof time.

In some embodiments, at least one processor may be configured to receivefrom the at least one sensor, during a current time period of expecteddiminished water usage, a real-time indications of water usage thatconstitutes a current water usage profile. At least one processor may beconfigured to compare the current water usage profile during theexpected period of diminished water usage with the at least one expecteddiminished water usage profile. At least one processor may be configuredto determine, based on the comparison, that water usage in the currentwater usage profile materially exceeds water usage in the at least oneexpected water usage profile.

In some embodiments, at least one processor may be configured to executea remedial action when, based on the comparison, the current water usageprofile materially exceeds the at least one expected water usageprofile. At least one processor may be configured to receive from the atleast one sensor, during a period when at least one appliance within thewater infrastructure may be in non-use, a current water usage profile.The at least one processor may be configured to compare the currentwater usage profile with the at least one expected water usage profile.The at least one processor may be configured to determine, based on thecomparison, whether the current water usage profile does notsubstantially correspond to the at least one known water usage profile.

In some embodiments, the at least one processor may be configured togenerate an abnormal consumption indication signal when, based on thecomparison, the current water usage profile does not substantiallycorrespond to the at least one known water usage profile. A currentwater event profile that is sensed in some distributed waterinfrastructure may be compared to a normal event profile using amathematical operation that outputs a quantitative measure of similarityor dissimilarity between the two profiles. A current event profile maybe said to not substantially correspond to the normal event profile ifthe measure of similarity or dissimilarity lies beyond the acceptablelimits of correspondence that may be defined for the normal eventprofile. The acceptable limits of correspondence may be expressed by astandard deviation or variance or any other quantitative measure ofspread defined over the numerical representation of the normal waterevent profile.

In some embodiments, at least one sensor of the system has a resolutionof at least 0.2 liters per hour. In a preferred embodiment, the at leastone sensor of the system has a resolution of greater than 0.2 liters perhour. Sensors with a resolution of less than 0.2 liters per hour maystill detect abnormal water consumption, but with less accuracy. In oneembodiment, at least one sensor of the system has a resolution of oneof: at least 0.1 liters per hour, at least 0.05 liters per hour, and atleast 0.01 liters per hour.

In some embodiments, at least one expected water usage profile mayinclude a plurality of profiles each associated with a differing periodof expected diminished water usage, wherein during comparing, thecurrent water usage profile may be compared with an expected diminishedwater usage profile corresponding to a time period of the current waterusage profile.

In some embodiments, at least one of the expected diminished water usageprofiles may correspond to a night time period when substantially nonormal water usage is expected in the distributed water infrastructure.At least one expected diminished water usage, during night time, maytake into account automated consumption of water from appliances andperiodically occurring irregular uses.

In some embodiments, at least one processor may be configured duringcomparing, to compare the current water usage profile with at least onepreset water usage profile that corresponds to a leak. The at least onepreset water usage profile may correspond to a leak of at least 0.2liters per hour.

In some embodiments, a remedial action may include generating anabnormal consumption alert. At least one processor may be configured,during comparing, to compare the current water usage profile with atleast one preset water usage profile that corresponds to a waterappliance, wherein the remedial action may include generating anabnormal consumption alert indicating a use of the water appliance.

An aspect of some embodiments may include a system for detectingabnormal consumption in a distributed water infrastructure. The systemmay include at least one processor. At least one processor may beconfigured to receive, from a water sensor upstream of a plurality ofwater appliances in the distributed water infrastructure, overall waterconsumption measurements. At least one sensor may have a resolution ofless than two liters per hour. The at least one processor may beconfigured to determine periods when the distributed waterinfrastructure may be in an inactive state of substantial non-use ofwater appliances. The at least one processor may be configured to trackwater consumption during a plurality of times when the distributedliquid infrastructure is in an inactive state.

In some embodiments, at least one processor may be configured to detectan upward trend in water consumption over the plurality of times. The atleast one processor may be configured to initiate remedial action whenan upward trend is detected. Remedial action may include generating anabnormal consumption alert.

In some embodiments, at least one processor may be configured toautomatically determine periods when the distributed waterinfrastructure is in an inactive state and water appliances are insubstantial non-use. At least one processor may be configured todetermine periods when the distributed water infrastructure is in aninactive state by accessing a timetable stored in memory, wherein thetimetable may include times of inactivity supplied by an administrator.The periods when the distributed water infrastructure is in an inactivestate or substantial non-use may include a non-zero continuous baselineof water usage. The at least one processor may be configured toconstruct an expected water event profile for consumption of waterduring the inactive state. The at least one processor may be configuredto compare a current overall water consumption measurements with anexpected water event profile for the consumption of water during theinactive state. The at least one processor may be configured to storeindications of a plurality of expected periods of substantial waterinactivity and to initiate remedial action when a decrease is detectedin an overall number of actual periods of substantial water inactivity.

FIG. 7 illustrates an exemplary method 700 for detection of abnormalconsumption with low volumes of water consumption. The operations ofmethod 700 discussed herein are intended to be illustrative. In someembodiments, method 700 may be implemented with one or more additionaloperations not described, and/or without one or more of the operationsdiscussed. Additionally, the order in which the operations of method 700are illustrated in FIG. 7 and described herein is not intended to belimiting.

In some embodiments, method 700 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all of the operations of method 700 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more of the operations ofmethod 700.

In some embodiments, at operation 710, at least one processor may beconfigured to receive from at least one sensor associated with thedistributed water infrastructure, indications of regular water usage,wherein the distributed water infrastructure may include a plurality ofwater appliances. At operation 720, at least one processor may beconfigured to determine, from the indications received over a timeperiod, at least one recurring time period of expected diminished waterusage. At operation 730, at least one processor may be configured todetermine, for the at least one recurring time period of expecteddiminished water usage, at least one expected diminished water usageprofile. At operation 740, at least one processor may be configured toreceive, from the at least one sensor during a current time period ofexpected diminished water usage, real time indications of water usagethat constitutes a current water usage profile.

At operation 750, at least one processor may be configured to comparethe current water usage profile during the expected period of diminishedwater usage with the at least one expected diminished water usageprofile. At operation 760, at least one processor may be configured to,based on the comparison, determine that water usage in the current waterusage profile materially exceeds water usage in the at least oneexpected water usage profile. At operation 770, at least one processormay be configured to execute a remedial action when, based on thecomparison, the current water usage profile materially exceeds the atleast one expected water usage profile.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, wherein the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits provided byevent-based leak detection systems and methods. In some embodiments, ameasurement of the number of liters consumed as a function of time maybe transformed into a water usage pattern that has a particularfingerprint or water usage pattern. A water usage pattern may bedetermined by any method consistent with identification herein, such asthe non-limiting examples of: event-based threshold method, guidedmachine learning, or automatic machine learning. Water usage patterndetermination may be assisted by a neural network, whereby a system mayprogressively improve performance to determine, identify, and comparewater usage patterns by considering examples. In some embodiments, aneural network may be used without task-specific programming.

In various alternative methods, detection of abnormal consumption withlow volumes of water consumption may be implemented by alternativemethods of receiving water information, and employing event-based leakdetection systems and methods to provide granularity of water usage toan end user.

Exemplary Embodiments of Abnormal Consumption Detection with Remainderafter Subtracting Known Events

The present application may provide for leak detection by identifying aremainder after subtracting known events. In a distributed waterinfrastructure such as an office building, many water events regularlyoccur simultaneously, increasing the challenge in detecting an anomaly.A potential benefit of systems and methods of the present disclosure mayinclude subtracting all detected known events from an overallinfrastructure profile and examining the remainder to determine if theremainder is likely attributable to a leak.

An aspect of some embodiments may include a system for detectingabnormal consumption in a distributed water infrastructure. The systemmay comprise at least one processor. In some embodiments, the at leastone processor may be configured to receive from at least one sensorassociated with the distributed water infrastructure indications of acurrent overall water usage profile in the distributed waterinfrastructure. The at least one processor may be configured to access adatabase of individual water usage profiles associated with waterappliances in the distributed water infrastructure. The at least oneprocessor may be configured to determine at least one individual waterusage profile that makes up the current overall water usage profile. Theat least one processor may be configured to segment the at least oneindividual usage profile from the current overall usage profile.

In some embodiments, the at least one processor may be configured toanalyze data associated with the segmenting to determine whetherabnormal consumption may be occurring in the distributed waterinfrastructure. The at least one processor may be configured to generatean abnormal consumption signal when likely abnormal consumption isdetermined.

In some embodiments, segmenting may include subtracting the at least oneindividual liquid usage profile from the overall liquid usage profile toobtain a remainder. Analyzing may include determining whether theremainder may be indicative of abnormal consumption. The database ofindividual water usage profiles may be generated from the history of atleast one sensor associated with the distributed water infrastructure.The individual water usage profiles in the database may be confirmed byan end user. An individual water usage profile may include a group ofwater usage profiles

Exemplary Embodiments of Ignoring Abnormal Consumption

The present application may provide for a feature for an end user toignore certain leak notifications. Not all leak notifications arenecessarily important leaks, or may be misidentified as a leak. Thesenotifications may annoy or distract an end user. A potential benefit ofsystems and methods of the present disclosure may include permittingadministrators, after receiving notification of a potential leak, tohave the ability to remotely instruct the system to ignore a leak.

An aspect of some embodiments may include a remote communicationoverride abnormal consumption detection system for a distributed waterinfrastructure. The system may comprise at least one processor. The atleast one processor may be configured to receive water usage informationfrom at least one sensor regarding a distributed water infrastructure.The at least one sensor may be associated with the distributed waterinfrastructure. For example, the sensor may be associated with a pipe inthe distributed water infrastructure. The sensor may be partially, orcompletely, within the pipe or outside the pipe.

In some embodiments, the at least one processor may be configured todetermine from the water usage information an event likely to be anabnormal consumption within the distributed water infrastructure. The atleast one processor may be configured to send via a transmitter amessage to an administrator notifying the administrator of the likelyabnormal consumption, and providing to the administrator data associatedwith the likely abnormal consumption.

A message refers generally to any information sent by the system. Thesystem may send a message in the form of two-way data packages. Two-waydata packages may be transmitted and received, either continually, orintermittently, between the system and the administrator. Exemplarymessage contents may include, but are not limited to, informationregarding water consumption data, water quality, appliance usage, andhealth profile.

Data associated with the likely abnormal consumption may include, butare not limited to, a current water consumption profile that may besensed in a distributed water system. Data associated with likelyabnormal consumption may include information that the current conditionswithin the distributed water infrastructure meet the conditions of astored abnormal water event. In some embodiments, data associated withthe likely abnormal consumption may include a current water consumptionprofile, pre-learned water consumption profiles that characterize normalconsumption, and any definitions of acceptable distance limits between apre-learned consumption profile and a current water consumption profile.

In certain instances, a customer or an administrator may find anabnormal water event to be acceptable. In such circumstances, a customermay not want to be bothered by continual reminders or alerts for theabnormal water event. The at least one processor may be configured toreceive from the administrator via the receiver a command to ignore thelikely abnormal consumption indication. The at least one processor ofthe system may be configured to receive, in response to the transmittedmessage, a command to close a valve.

A command to ignore may be generated by the administrator or by thecustomer to signal the system that an abnormal alert has been receivedand the administrator, or customer, prefers to ignore the abnormal waterconsumption event. A remote communication override abnormal consumptiondetection system may permit water to flow through the valve after theignore command is received.

In some embodiments, the processor may be configured to store a profileof the likely abnormal consumption associated with the ignore abnormalconsumption command received from the administrator, and to avoidsending a subsequent likely abnormal consumption message to theadministrator the next time a likely abnormal consumption matches thestored profile.

In some embodiments, the system may store a water profile in anonvolatile memory (NVM) device. A stored profile may include any of awater consumption profile, a time stamp, a water flow rate, and anywater quality information, as well as appliance usage and healthprofile.

In some embodiments, the system may be configured to avoid customerharassment and have a low false alarm rate. The system may have logic toreduce the number of alerts and use an effective messaging system withfewer alerts.

In some embodiments, the data provided to the administrator may includeat least one of flow rate and flow volume of the likely abnormalconsumption. The data provided to the administrator may include locationinformation for the likely abnormal consumption. Gathering the locationinformation for the likely abnormal consumption may be a functionimplemented in the cloud in order to get an overall geographical viewabout any abnormal consumption distribution. The system may provideinformation that may be used to initiate a water service for customers.A water service provider or residence may use information gathered bymultiple sensors to identify that some appliances that are within ageographic location are malfunctioning.

In some embodiments, the data provided to the administrator may includean indication of an identity of a malfunctioning appliance. Anindication of an identity of a malfunctioning appliance may be based ona deviation beyond a certain threshold level from a normal pattern ofthe appliances. A normal pattern may include all the information thatdefines and indicates the normal functioning of the appliance. Exemplaryinformation may include information related to flow, usage, time, waterpatterns, vibration, and any health profile of the water-consumingdevice.

In some embodiments, at least one processor may be configured to provideupdated data to the administrator following an initial alert in order toenable the administrator to assess ongoing severity. Abnormal waterconsumption may only last for a period of time before stopping. Forexample, a leak in an irrigation system may only occur when theirrigation system is in use. The processor may be configured to provideupdated data to the administrator following an initial alert in order toenable the administrator to determine if the likely abnormal consumptionhas self-mitigated. An abnormal water consumption event that hasself-mitigated may refer to a situation where the system, eitherautomatically or under the direction of an administrator, has taken anaction that mitigates and reduces the severity of the event. Once therisk to property or appliance or degradation in appliance performancehas been mitigated or corrected, the system may inform the administratorthat the adverse event is resolved.

In some embodiments, the processor may be further configured to close asystem-wide valve in response to a command to close the valve. Asystem-wide valve refers generally to at least one valve that maycontrol the distribution of water through the system. In otherembodiments, the system-wide water consumption may be controlled throughmechanisms other than a valve. For example, water consumption may behalted by diverting water to an emergency reservoir.

In one embodiment, a system may support several water consumptionconfigurations. A distributed water infrastructure may comprise a mainwater pipe system with a large diameter at an entrance to a largebuilding, and small diameter water pipe systems for each floor. In someembodiments, a system-wide valve may control the water flow through ahouse or single building. A system-wide valve may control water flowthrough a floor of a building or to a particular room.

In some embodiments, the at least one processor may be furtherconfigured to close a sub-system valve in response to a command to closethe valve. The at least one processor may be configured to close asystem-wide valve if neither a close valve or an ignore command isreceived within a predetermined time period following messagetransmission to the administrator. In some embodiments, a predeterminedtime period may be at least 30 seconds, at least 1 minute, at least 5minutes, at least 10 minutes, at least 15 minutes, at least 30 minutes,and at least 45 minutes. In some embodiments, the predetermined timeperiod may be one of: at least 1 hour, at least 2 hours, at least 3hours, at least 5 hours, at least 10 hours, and at least 24 hours. Thepredetermined time period may depend on the type of abnormal water eventdetected. A predetermined time period may be relatively short if theabnormal water event is determined to consume a large amount of water. Apredetermined time period may be relatively long if the abnormal waterevent is determined to consume a small amount of water. A predeterminedtime period may be set by a consumer. The system may have a built-inmechanism to control the period of time before a reminder is transmittedto a consumer, or to control length of the predetermined time period toclose a system-wide valve.

An advantage of some embodiments may be the ability of a system tocommunicate to a remote user. A remote user may be informed of anemergency even if in a remote location, and address the emergency fromthe remote location. The transmitter may be a remote communicationtransmitter and the receiver may be a remote communication receiver.

Exemplary Embodiments of Self-Monitoring Water Appliances

The present application may provide for a system that monitors theperformance of water appliances. Some water-using appliances maydeteriorate in performance after a certain amount of time. An aspect ofthe disclosure may be directed to water appliances such as washingmachines and dishwashers that are able to check their own health bymonitoring deviations from normal water usage profiles. It is envisionedthat this process may be performed at the level of a distributed waterinfrastructure, or at the level of an individual appliance.

Some water-using appliances may deteriorate in performance after acertain amount of time. This deterioration may be in the form of anincrease in the amount of water consumed during the operation of theappliance. For example, some part of the water appliance may be leaking.The water appliance may be required to consume more water before theappliance ceases operation. The deterioration of a water appliance maybe apparent from a decrease in the amount of water consumed during theoperation of the application. For example, the water appliance may beclogged such that water does not flow properly into the appliance. Thewater appliance may not need to demonstrate either an increase ordecrease in water consumption, but the flow of water into the appliancemay show a difference from a normally operating appliance. For example,an appliance may be clogged, or have a loose valve such that the amountof water flow oscillates over time, even though the total amount ofwater consumed by the device does not differ from that of a normallyoperating device.

An aspect of some embodiments may include a water-using appliance. Thewater-using appliance may comprise an inlet for connection to a watersource, and a water outlet. A water-using appliance may be any devicethat takes water as an input and discards water as an output. Theappliance might enhance the water inputted via an enhancement process(e.g. filter, or ultraviolet purification system). The appliance output(water outlet) may be an input for other appliances, faucets, or taps.Examples of water-using appliances range from faucets, mini-bars,washing machine, dishwasher, or industrial machinery. A water sourcerefers generally to the input for a water-using appliance. The watersource may be any inlet that provides water for a water-using appliance.The water source may be a major water main that provides water to awater-using appliance. The water source may be a source of water insidea building proximate to the water-using appliance. A water outlet refersto an outlet that water exits after water has passed through the device.Water-using appliances may have specific piping where water goes afterthe water-using appliance has finished its use of the water. The wateroutlet may be a drain, sewer, or another water-using appliance. In someembodiments, a water-using appliance may be any appliance that includesa chamber between a water inlet and a water outlet, where the chambermay be configured to enable water to be employed as part of a process.For example, a water using appliance comprising a chamber may include awashing machine, a wet carpet cleaner, and an ice machine.

In one embodiment of the water appliance, at least one sensor may beintegrated into the appliance for monitoring water usage of theappliance. Memory may be integrated into the appliance for storing waterusage information indicative of normal operation of the appliance. Awater-using appliance may have the ability to retain useful water usageinformation that can help the appliance be monitored (eitherindependently or from a central source) for proper usage.

In some embodiments, at least one processor may be integrated with theappliance. An integrated processor refers to a processor that isincluded with the appliance. The processor may be within the water-usingappliance. In other embodiments, the processor may be enclosed within aseparate container that may be part of the appliance. The water-usingappliance may be configured to accept the addition of a processor. Forexample, any sensor within the appliance may be configured to be easilyaccessed by a processor to accept or store data. In some embodiments, anintegrated processor may be either built into the water-using applianceduring manufacturing or may be added at a later point.

A processor may be configured to receive, from the at least one sensor,current water usage information. Water usage information refers to anymeasurements related to the water consumption by the water-using device,and may include the water flow rate or the total consumption over time.The measurement of water usage may be monitored and tracked to very lowlevels of flow over time. A processor may compare the current waterusage information with water usage information stored in memory todetermine an existence of a substantial deviation. “Substantialdeviation” as used herein refers to a measurement of deviation from thenormal expected usage for each water-using appliance. A substantialdeviation from the normal expected usage can help determine proper usageand efficiency of the water-using appliance. The processor may beconfigured to initiate remedial action if a substantial deviationexists.

Initiating remedial action refers to the process where the substantialdeviation moves beyond a certain threshold causes an action to occur. Insome embodiments, a remedial action can be an alert, an email, or even ashutdown of the water-using appliance. The nature of an action may bedetermined by the rules associated with each water-using device.

In some embodiments, a water-using appliance may comprise an inlet forconnection to a water source, a water outlet, a chamber between theinlet and the outlet configured to enable water to be employed as partof a process, at least one sensor integrated into the appliance formonitoring water usage of the appliance, memory integrated into theappliance for storing water usage information indicative of normaloperation of the appliance, at least one processor integrated into theappliance, the at least one processor configured to: receive from the atleast one sensor current water usage information, compare the currentwater usage information with water usage information stored in memory todetermine an existence of a substantial deviation, and initiatingremedial action if a substantial deviation exists.

The appliance may also be configured to initiate remedial action such asproviding information about options to repair and/or replace thewater-using appliance. Remedial action may include providing informationabout options to repair and/or replace the water-using appliance. Insome embodiments, a remedial action available for a water-usingappliance may include a recommendation to repair or replace a part thathas crossed the substantial deviation threshold. This recommendationmay, based upon recommended norms of usage, other data gathered onsimilar devices, or pattern analysis.

Exemplary Embodiments of Differentiating Between Irrigation andNon-Irrigation Events

A potential benefit of some embodiments of the present disclosure mayinclude differentiating between irrigation and non-irrigation events.Many commercial and residential properties have irrigation systems thatuse high volumes of water for extended periods. Those examining flowrates and/or volumes might misinterpret an irrigation event as a pipeburst. An aspect of the present disclosure may be directed to overcomethis issue by analyzing and storing water usage profiles for irrigationevents. When high-volume water usage is detected, a profile of thatusage can be compared with known profiles of irrigation events. If thereis a match, no remedial action may be taken.

An aspect of some embodiments may include a system for enabling remedialaction in response to detecting abnormal consumption in a distributedwater infrastructure, which may include irrigation and non-irrigationappliances. The distributed water infrastructure may contain onlyirrigation appliances. Alternatively, the distributed waterinfrastructure may contain only non-irrigation appliances. For example,a system that is useful for identifying irrigation events may also beuseful for identifying any high-volume water usage. The water usage maybe infrequent, like the infrequent refilling of a swimming pool.

In some embodiments, the system may receive from at least one sensorassociated with the distributed water infrastructure signals indicativeof water usage in the distributed water infrastructure. The system may,based on the signals, construct a plurality of water event profiles. Thesystem may characterize at least one of the plurality of water eventprofiles as an irrigation water event profile, and store the at leastone irrigation water event profile in memory. The system may receivefrom at least one sensor, current signals indicative of current waterusage in the distributed water infrastructure. The system may constructa current water event profile based on the signals indicative of currentwater usage. The current water event profile may share characteristicswith an abnormal consumption in the distributed water infrastructure.

In some embodiments, the system may compare the current water eventprofile with at least one irrigation water event profile stored inmemory. When the current water event profile substantially matches theat least one irrigation water event profile, the system might notinitiate remedial action. The system might not initiate remedial actiondespite detecting that a current water event profile sharescharacteristics with abnormal consumption in the distributed waterinfrastructure, because the current water event profile matches a knownexception.

In some embodiments, a system for enabling remedial action in responseto detecting abnormal consumption in a distributed water infrastructurethat may include irrigation and non-irrigation appliances, may receivefrom at least one sensor associated with the distributed waterinfrastructure signals indicative of water usage in the distributedwater infrastructure. The system may, based on the signals, construct aplurality of water event profiles, and characterize at least one of theplurality of water event profiles as an irrigation water event profile.The system may store the at least one irrigation water event profile inmemory. The system may receive, from the at least one sensor, currentsignals indicative of current water usage in the distributed waterinfrastructure, and construct a current water event profile based on thesignals indicative of current water usage, wherein the current waterevent profile shares characteristics with an abnormal consumption in thedistributed water infrastructure. The system may compare the currentwater event profile with the at least one irrigation water event profilestored in memory, and when the current water event profile substantiallymatches the at least one irrigation water event profile, avert remedialaction despite the current water event profile sharing characteristicswith abnormal consumption in the distributed water infrastructure.

In some embodiments, the at least one processor may be furtherconfigured to initiate remedial action if the current water profile doesnot substantially correspond to the at least one irrigation water eventprofile. The remedial action may include sending a notification to asystem administrator and providing the system administrator with anability to remotely control a valve in the distributed waterinfrastructure.

In some embodiments, an irrigation event may demonstrate a relativelylarge spike in the amount of water consumed relative to non-irrigationconsumption. An irrigation event may be differentiated fromnon-irrigation events by a significantly higher flow rate of water. Theflow rate of water during an irrigation event may be at least one of:10%, 20%, 30%, 40%, 50%, 100%, 150%, or 200% larger than regularnon-irrigation water consumption. The flow rate of water during anirrigation event may be greater than 200% of normal water consumption.The system for initiating remedial action may identify issues with theirrigation system by determining that a water consumption event is anirrigation event, but that the water consumption varies in at least oneof flow rate and flow volume, as compared to a normal irrigation event.

In some embodiments, the water irrigation profile may include a 50-100ml of water flow in no more than at least one of 0.1, 0.15, 0.18, 0.2,0.3, 0.4, and 0.5 seconds. The water irrigation profile may include a50-100 ml of water flow in less than 0.18 seconds. The water irrigationprofile may include 100+ ml of water flow in less than 0.18 seconds. Thewater irrigation profile may include a 100 ml of water flow in less than0.18 seconds. The water irrigation profile may include a 50 ml of waterflow in less than 0.18 seconds. The water irrigation profile may includea 75 ml of water flow in less than 0.18 seconds.

Exemplary Embodiments of Health and Lifestyle Predictions Based onDetected Water Usage

An aspect of some embodiments may include utilizing a recognizedcorrelation between water usage and a resident's health and lifestyle.For example, if during a period when a resident is expected to be athome, water usage goes to zero, it may be an indicator that the residentis incapacitated, and remedial action may be initiated. A dramaticincrease in toilet flushes may be an indicator of a gastrointestinaldisorder, and remedial action may be initiated. A tap left running maybe an indicator of dementia, and remedial action may be initiated. Theindicator may be general to all consumers. The indicator may be appliedonly to users as requested or determined by a user. The indicator may bebased on a particular consumer's usage patterns. For example, if theresident has a usual pattern of water usage during specific times of theday, deviations from that schedule may be used to help inform whetherthere is any change in the resident's health or lifestyle.

An aspect of some embodiments may include a detection system for adistributed water infrastructure, where the system may be configured todetermine at least one of a human health or lifestyle state from waterusage patterns in the distributed water infrastructure. A detectionsystem may be to any apparatus that can sense water usagecharacteristics, and may include a water meter of any kind, a watersensor, or a plurality of water sensors. A water usage pattern may be acollection of signals that form an identifiable or unique combinationthat can be associated to a specific water usage.

The ability to identify and track the frequency that water consumers usecertain water appliances enables the ability to associate humanbehavior, health condition, and life style to one or more water usagepatterns (or a lack of usual water usage patterns). For example, a waterusage pattern associated with a bath/shower may be used to determinehealth conditions according to the following exemplary factors: theindication of a bath, bath versus shower, length of shower, or not usingthe bath for a long period of time. Any of these factors may be usedalone or in combination, together or with other factors, including theabsence of such factors, to determine the health or hygiene of aparticular water consumer.

For example, a water usage pattern associated with a toilette may beused to generate information on the frequency of use of the toilette. Byway of example, such information on the frequency of use of the toilettemay indicate that there is a digestive or bladder problem.

The combination of multiple water usage patterns can be used toholistically determine the water consumer's health. For example, thewater user's hygiene habits can be determined if there is a signal forwashing hands after flushing the toilet. The frequency of handwashing,or the time of day that concentrates handwashing versus not using waterat all, may indicate wake-up times or going to sleep times.

In some embodiments, water appliance usage and frequency may be used todetermine a water consumer's health or lifestyle. For example, thefrequency that a liquid dispenser, such as a water bar, kiosk, or coffeemachine is used may indicate whether the water user is well hydrated.The usage of a laundry machine or dishwasher may be an indicator for awater consumer's lifestyle or health. The use of water for irrigationmay be an indicator for a water consumer's lifestyle or health.

In some embodiments, other factors aside from health and lifestyle canbe determined from the water usage information. For example, water usageinformation may be used to determine the number of cars in an automatedcar washing facility, the amount of time that an office was active, orthe amount of time a cleaning team took to wash something. Additionally,the system may be able to detect fraudulent usage of water. For example,the use of water when it is expected that no water should be used mayindicate theft of water.

In some embodiments, a detection system may comprise at least oneprocessor. The at least one processor may be configured to receive fromat least one sensor associated with the distributed water infrastructuresignals indicative of water usage in the distributed waterinfrastructure.

In some embodiments, the at least one processor may be configured todetermine detected patterns of signals. The at least one processor maybe configured to access a database of a plurality of stored water usagepatterns, where each stored water usage pattern may be associated withat least one human health or lifestyle state. A database may refer tophysical memory that can be either locally in a computer, including anysystem with memory and a computing device, and storage services in acloud. A water usage pattern can be stored in any type of database. Thedatabase can be accessed in a real-time situation or in non-real-timesituations in order to retrieve data, such as water usage patterns.

In some embodiments, each stored water usage pattern may be associatedwith at least one human health or lifestyle state. Not every water usagepattern may be associated with at least one human health or life style.In some embodiments, a combination of patterns may provide an indicationof human behavior. For example, significant change in a single waterusage pattern (such as a longer than average shower) may indicate achange in lifestyle or health state. A combination of patterns (such asa toilette flush with or without hand washing and the frequency oftoilette flushes) may indicate a change in lifestyle or health state.

In some embodiments, the at least one processor may be configured tocompare at least one detected pattern with at least some of theplurality of stored water usage patterns. The at least one processor maybe configured to, based on the comparison, determine that at least onedetected pattern substantially corresponds to at least one of theplurality of stored water usage patterns in the database.

In some embodiments, the at least one processor may be configured toinstitute a remedial action for a human health or lifestyle stateassociated with the at least one stored water usage patterns. A systemmay be configured to establish a baseline of normal behavior, andprovide an indication if a pattern or plurality of patternssubstantially divert from the normal. As a non-limiting example, aregular shower-length average as detected in a specific house may be 7minutes with a standard deviation of 3 minutes, so if a detected showerlength is three standard deviations greater than the average showerlength, the system may initiate a remedial action.

In some embodiments, systems and methods according to the presentdisclosure, may employ and/or create rules to indicate a human state. Asa non-limiting example, a manual or automatic method may determine thata frequency of toilette flushes during night hours greater than somenumber (x) may be abnormal, and be a possible indication for prostateproblem. As a non-limiting example, a manual or automatic method maydetermine that the lack of toilette flushes during morning hours in anoccupied apartment in an elderly care facility may be abnormal andinitiate a remedial action. If an abnormal activity indicates a possiblelife-threatening condition, a remedial action may be to immediately tryto contact the tenant.

In some embodiments, one of the plurality of stored usage patterns mayinclude a signal indicating that hands are washed after using thetoilets. A toilet flush may have a distinctive, easy to recognize,repeatable pattern of water usage. A basic hygiene practice is that,after every use of toilets, people must wash their hands properly inorder to prevent the transfer of germs and other communicative diseases.In some embodiments, washing hands also creates a clear pattern of waterusage. The lack of a washing hands pattern in conjunction with a toiletsflush pattern can indicate an unhealthy habit. A washing hand patternthat has volume or duration less than a specific threshold can alsoindicate the same. Such indication in a food industry facility shouldraise an immediate alarm and a corrective action.

In some embodiments, one of the plurality of stored usage patterns mayinclude an extended period of non-water use wherein the associatedhealth state may be an individual's incapacity, where the remedialaction may be to send a message to a contact indicating the probableincapacity. A message may be sent to any individual, group ofindividuals, safety system, security system, network operation center,or any other entity that has interest on receiving data and alerts fromthe system.

In some embodiments, an extended period of non-water use may indicatethe incapacity of an end user. Healthy life habits involve regular useof water. A typical day for a healthy individual usually includes usingwater for flushing toilets, washing hands, washing dishes, drinking,taking a shower, cleaning the house, etc. An irregular or extendedperiod of non-water usage might give an early warning of a health stateor even an acute state of incapacitation. Sending an alert during anirregular period of non-water usage may be a non-intrusive way tomonitor the health of an at-risk person.

In some embodiments, one of the plurality of stored usage patterns mayinclude an amount of water usage below a threshold, where the associatedhealth state may be unhealthiness and the remedial action may be to senda message to a remote recipient indicating the probable unhealthiness. Areduction of water usage or a reduction of a certain water usage or theabsence of certain water usage might give an early warning of a healthstate or even an acute state of incapacitation.

In some embodiments, one of the plurality of stored usage patterns mayinclude leaving on a water-using device past a threshold, where theassociated health state may be dementia and the remedial action may beto send a message indicating a probability of dementia. Leaving thewater running beyond the usual average usage can indicate that one hasforgot to turn it off or lost the ability to do so. A threshold could beset up for each type of usage based upon the average or any type ofprior knowledge. The water-using device may be a faucet.

In some embodiments, one of the plurality of stored usage patterns mayinclude a number of toilet flushes above a threshold, where theassociated health state may be a digestive disorder and the remedialaction may be to send a message indicating a probable digestivedisorder. A digestive disorder may be a health condition that is usuallyassociated with unusual use of water such as increasing visits to thetoilettes, shower, and washing of hands.

Frequency of toilette flushes during night hours greater than a certainamount may indicate possible prostate problems. Alternatively, the lackof toilette flushes during morning hours in an occupied apartment in anelderly care facility may indicate a possible life-threateningcondition, and may trigger a remedial action to immediately try tocontact the tenant.

In some embodiments, the processor may be further configured todetermine from water usage patterns when an inhabitant is likely awayfrom home and to suspend comparing during away periods. Some usagepatterns are associated with automated machines (i.e. laundry,dishwasher, automated irrigation, etc.) and others with human behavior(toilette, faucet usage, shower, etc.).

If for a period of x minutes or more human usage of water is notdetected then one may conclude that the tenants are away or sleeping.The time of day can give a good indication for the former or the later.The x minutes can be a fixed number or can be learned from the past,manually, or by automated machine learning.

FIG. 8a illustrates an exemplary method 800 for estimating a health andlifestyle status based on water consumption. The operations of method800 discussed herein are intended to be illustrative. In someembodiments, method 800 may be implemented with one or more additionaloperations not described, and/or without one or more of the operationsdiscussed. Additionally, the order in which the operations of method 800are illustrated in FIG. 8a and described herein is not intended to belimiting.

In some embodiments, method 800 may be implemented in one or moreprocessing devices (e.g., a digital processor, an analog processor, adigital circuit designed to process information, an analog circuitdesigned to process information, a state machine, and/or othermechanisms for electronically processing information). The one or moreprocessing devices may include one or more devices executing some or allthe operations of method 800 in response to instructions storedelectronically on an electronic storage medium. The one or moreprocessing devices may include one or more devices configured throughhardware, firmware, and/or software to be specifically designed forexecution of one or more of the operations of method 800.

In some embodiments, at operation 810, at least one processor may beconfigured to receive from at least one sensor associated with thedistributed water infrastructure signals indicative of water usage inthe distributed water infrastructure. At operation 820, at least oneprocessor may be configured to determine from the signals indicative ofwater usage a current water usage pattern. At operation 830, at leastone processor may be configured to access a database of a plurality ofstored water usage patterns, wherein at least one stored water usagepattern may be associated with at least one human health or lifestylestate. At operation 840, at least one processor may be configured tocompare at least one current water usage pattern with at least some ofthe stored water usage patterns. At operation 850, at least oneprocessor may be configured to, based on the comparison, identify ahuman health or lifestyle condition reflected by the current water usagepattern. In some embodiments, at operation 860, at least one processormay be configured to institute a remedial action corresponding to theidentified human health or lifestyle state.

FIG. 8b illustrates an exemplary water usage pattern for detecting ahandwashing state after the use of a toilet. FIG. 8b shows a water usagesignal over time, with flow rate on the y-axis and time on the x-axis.FIG. 8b shows a water usage pattern 872 that may be determined to betoilet flushing. Water usage pattern 872 may be determined by any methodconsistent with identification herein, such as the non-limiting examplesof through a threshold method, guided machine learning, or automaticmachine learning. Water usage pattern determination may be assisted by aneural network, whereby a system may progressively improve performanceto determine, identify, and compare water usage patterns by consideringexamples. In some embodiments, a neural network may be used withouttask-specific programming.

Similarly to water usage pattern 872 for toilet flushing, water usagepattern 874 corresponding to handwashing may be measured and identified.FIG. 8b shows two overlapping water usage profiles, but in someembodiments, for example depending on the flow pattern of the toiletflushing and/or being refilled after flushing, overlapping water usageprofiles may not exist, and the water usage profiles may be distinct.Water usage pattern 874 might not be present, which would indicate thata user has not washed hands. The duration of water usage pattern 874 maybe shorter than some threshold period of time, which may indicate thathands were not thoroughly washed. Water usage patterns 872 and 874 mightnot be present, which may indicate that no users are within a household,and/or a user may be ill in the household.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, where the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor a parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits of event-basedleak detection systems and methods. In some embodiments, a measurementof the number of liters consumed as a function of time may betransformed into a water usage pattern that has a particular fingerprintor water usage pattern. A water usage pattern may be determined by anymethod consistent with identification describe herein, such as thenon-limiting examples of: event-based threshold method, guided machinelearning, or automatic machine learning. Water usage patterndetermination may be assisted by a neural network, where a system mayprogressively improve performance to determine, identify, and comparewater usage patterns by considering examples. In some embodiments, aneural network may be used without task-specific programming.

In various alternative methods, estimating a health and lifestyle statusbased on water consumption may be implemented by alternative methods ofreceiving water information, and employing event-based leak detectionsystems and methods to provide granularity of water usage to an enduser.

Exemplary Embodiments of Differentiating Between Multiple OverlappingWater Events

Traditionally, a single upstream water sensor may have difficultydifferentiating between water usage of multiple downstream waterappliances. A potential benefit of systems and methods of the presentdisclosure may be that some embodiments may address this issue byanalyzing water usage signals for a first sustained increase and a firststeady state plateau, followed by a second sustained increase and asecond plateau that leads to a total flow rate greater than the firstflow rate by itself. Each water consumption event may have its owncharacteristics. Therefore, when one of the events ends, the system maydetermine which of the overlapping events has ended by analyzing whichcharacteristics are missing from the continuing water usage. In analternative, a mixed event may be deconstructed into two or morecomponents by using inflection locations to deconstruct mixed events insubcomponents. In some embodiments, a subcomponent, from an overlappingevent that has been deconstructed, may be compared against prior storedsignatures of subcomponents.

In some embodiments, a system could may be configured to detect whenwater flow rate is above a certain threshold to be identified as a waterevent, identify the sustained increase in water flow rate as a firstevent, detect a second sustained increase above a second thresholdduring the first event, and identify a second event. If a drop isapproximately the same as the sustained increase of one of the sustainedincreases, the system may be able to identify which event has ended.

By way of a non-limiting example, if a shower is taken during a laundrycycle, and the shower consumes 2 gallons per minute, then theconsumption and cessation of water use by the shower can be determinedby an increase in water flow rate by 2 gallons per minute, and followedby a decrease in water flow rate by 2 gallons per minute. This proceduremay be performed when two or more simultaneous water consumption eventsoccur.

An aspect of the disclosure may be directed to a system fordifferentiating between overlapping water events in a distributed waterinfrastructure including a plurality of water appliances, the systemcomprising at least one processor. Overlapping water events are two ormore events that occur simultaneously or partially-simultaneously intime, in a distributed water system, where each event originates from aunique or identifiable water consumer connected to the water system.

In some embodiments, the at least one processor may be configured torepeatedly measure at least one overall water usage indicator of thedistributed water infrastructure, the at least one water usage indicatorincluding at least one of an overall flow rate and an overall flowvolume in the distributed water infrastructure. The overall flow rate ofthe water flowing in a distributed water system may be a measure of theaggregate flow rate of the water that may be flowing through all thewater consumers connected to the water system at any moment in time.

In some embodiments, repeated measuring occurs at a single locationupstream of the plurality of water appliances. At least one processormay be configured to detect a first sustained increase in the repeatedmeasurements.

The at least one processor connected to the distributed waterinfrastructure may detect a first significant increase in the flow ratethat corresponds to the use of a single water-consuming appliance in thedistributed water infrastructure. In some embodiments, a significantincrease in the flow rate may be an increase to a flow-rate that is overa minimum flow rate, which may represent the minimal normal flow ratedetected for all water consumers connected to the water system.

In some embodiments, the at least one processor may be configured tostore in memory a first indicator of the first sustained increase. Afirst indicator of the first sustained increase in flow rate may be aquantitative value that encapsulates the increase in flow-rate. Thisvalue may be, by way of non-limiting examples, an absolute flow rate, aflow rate difference, and a derivate thereof.

In some embodiments, the at least one processor may be configured toattribute in memory the first sustained increase to a first water eventin the distributed water infrastructure. Attribution may be done byassociating a sustained increase with a water event. Attribution mightnot include an indicator that is tied to a specific event, but rathermay be a general indicator that some event has occurred. The at leastone processor may attribute the first sustained increase to a firstwater event by storing the time that the first sustained increaseoccurred. The at least one processor may be configured to store inmemory the magnitude of the first sustained increase. Measures of themagnitude of the first sustained increase may be, for example, theaverage flow rate of the sustained increase and the duration of time forthe increase in flow rate to be sustained.

In some embodiments, the at least one processor may be configured toattribute the first sustained increase to a first water event withoutspecifying the source or type of water event. Any time that a sustainedincrease occurs, the at least one processor may be configured toidentify the type of water event that has occurred.

In some embodiments, attributing in memory a water event to the firstsustained increase may include identifying a particular applianceassociated with the first sustained increase. Attributing in memory thefirst sustained increase to a first water event may include accessingpreviously stored fingerprints of water events associated with knownappliances in the distributed water system, and determining a matchbetween at least one characteristic of the first sustained increase anda characteristic of a particular fingerprint.

In some embodiments, certain water events may have identifiablecharacteristics that may aid in the identification of that event, andthese identifiable characteristics, or fingerprints, may be stored inmemory. The stored fingerprints may be associated with known waterappliances. The stored fingerprints may be associated with a type ofwater use that is not specific to a single water appliance. The at leastone processor may be configured to identify a particular applianceassociated with the first water event-based on at least the firstindicator and the third indicator. The at least one processor may,during the first sustained increase, detect in the overall measurementsa second sustained increase.

A second significant increase in the flow rate in the aggregate flowrate signal may correspond to the use of a second water-consumingappliance in the distributed water infrastructure simultaneously withthe first water-consuming appliance whose sustained flow rate wasdetected earlier and may be ongoing. The at least one processor may beconfigured to, during the first sustained increase, detect in therepeated overall measurements a second sustained increase. The at leastone processor may be configured to store in memory a second indicator ofthe second sustained increase. The at least one processor may beconfigured to attribute, in memory, the second sustained increase to asecond water event in the distributed water infrastructure.

In some embodiments, the at least one processor may be configured to,following initiation of the first sustained increase and the secondsustained increase, detect in the repeated measurements a decrease inthe overall water usage indicator. A decrease in the overall water usageindicator may be a quantitative value that encapsulates the decrease inflow-rate that may include two or more consecutive signals indicative ofwater usage in a distributed water system. The signals may eachrepresent an aggregate measure of the water usage over allwater-consuming appliances that are connected to the system. This valuemay be measured as absolute flow rate or a flow rate difference or anyderivate thereof.

In some embodiments, the at least one processor may be configured toattribute a third indicator to the decrease. The process of attributinga third indicator may refer to the process of assigning and retaining aquantitative value representing the decrease in flow rate. This valuemay be the third one retained after two sustained increases in flowrate. By way of non-limiting example, this value may be an absolute flowrate, a flow rate difference, or any derivate thereof.

In some embodiments, the at least one processor may be configured tocompare the third indicator with at least one of the first indicator andthe second indicator stored in memory to determine a substantial matchand determine a cessation of at least one of the first water event andthe second water event. A substantial match between one of the twoprevious indicators of sustained increases in the overall consumptionand a third indicator of a decrease in the overall consumption may bedetermined by calculating a distance measure between the third indicatorand each of the first two indicators—to determine to which it may bemost similar and if it is similar enough based on whether the differenceis within some acceptable, pre-determined bounds. In this case, asubstantial match between the third indicator and the one most similarto it may be established. The distance measure used may be anyappropriate similarity or difference measure.

In some embodiments, the at least one processor may be configured toinitiate an action based on a cessation determination. A cessation ofconsumption from a particular consumer connected to the distributedwater infrastructure may be determined when a substantial match has beenfound between an indicator of a sustained decrease with a previousindicator of sustained increase in the overall consumption indicator.Once the end of an event has been determined an action may be taken,which may include storing all data about the event in a database,including, for example, the raw consumption signals, the volume, theduration, the start-time of the event and any derivatives of this data.The action may also involve triggering algorithms to determine the waterconsumer or appliance connected to the distributed water infrastructurefrom where the ended event originated.

In some embodiments, the initiated action may include recording, inmemory, usage of at least one of the plurality of water appliances. Theinitiated action may include transmitting an alert to a remote locationindicating the water event.

An aspect of the disclosure may be directed to a system fordifferentiating between overlapping water events in a distributed waterinfrastructure including a plurality of water appliances, the systemcomprising at least one processor configured to repeatedly measure atleast one overall water usage indicator of the distributed waterinfrastructure. The at least one water usage indicator may include atleast one of an overall flow rate and an overall flow volume in thedistributed water infrastructure. In the repeated measurements, theprocessor may be configured to detect a first sustained increase, storein memory a first indicator of the first sustained increase, attributein memory the first sustained increase to a first water event in thedistributed water infrastructure. During the first sustained increase,the at least one processor detect in the repeated overall measurements asecond sustained increase, store in memory a second indicator of thesecond sustained increase, attribute in memory the second sustainedincrease to a second water event in the distributed waterinfrastructure. Following initiation of the first sustained increase andthe second sustained increase, the at least one processor may detect, inthe repeated measurements, a decrease in the overall water usageindicator, attribute to the decrease to a third indicator, compare thethird indicator with at least one of the first indicator and the secondindicator stored in memory to determine a substantial match, therebydetermining a cessation of at least one of one of the first water eventand the second water event, and initiate an action based on thecessation determination.

In some embodiments, the first sustained increase may be an increasebeyond a first threshold. A first threshold may be a quantitative valuedefining the minimum acceptable increase in flow rate for a first eventto be considered legitimate. This value may be determined using priorknowledge about the sustained flow rates of other legitimate consumptionevents occurring on their own in a distributed water infrastructure. Forexample, a threshold may be a percentage, an amount above signal tonoise, or an amount that may be above the smallest amount of water.

In some embodiments, the at least one processor may be configured todetermine the first threshold by aggregating water usage data of waterappliances known to be currently operating in the distributed waterinfrastructure. A first threshold may be determined to be less than thesmallest water consumer in a distributed water infrastructure.

In some embodiments, the second sustained increase may be an increasebeyond a second threshold associated with the second sustained increase.A second threshold may be a quantitative value defining the minimumacceptable increase in flow rate for a second event, which begins whilea first event may be ongoing, in order to be considered legitimate. Thisvalue may be determined using prior knowledge about the increase in flowrates of legitimate consumption events that start while a first eventmay be ongoing in the same distributed water infrastructure.

In some embodiments, the first threshold and the second threshold aresubstantially equal. The threshold associated with the first sustainedincrease and the threshold for the second sustained increase may bebetween 0.001 and 10 liters/minute. The threshold may be between 0.01and 1 liters/minute. The threshold may be approximately 0.1liters/minute. The first threshold and the second threshold may be lessthan about 1 liter/hour.

In some embodiments, the indicator may be a pattern of water usage overa period of time. The indicator might not be a single indication, andmay also include indicators that occur during an extended period of timeduring the first sustained increase. By way of non-limiting example, anexemplary indicator may be the average flow rate during the firstsustained increase. At least one of the first sustained increase and thesecond sustained increase may include a pattern that varies over time.By way of non-limiting example, an exemplary indicator may be thepattern for washing machine.

In some embodiments, prior to the first sustained increase, at least oneprocessor may be configured to detect an initial spike in water usage,and to attribute in memory the first sustained increase to the firstwater event if the spike is detected.

An initial spike in a pattern of water usage may be a rapid increase inflow rate that occurs at the beginning of the pattern when a waterconsumer or appliance connected to a distributed water infrastructurestarts to consume water. This spike might not represent the actual flowrate that the consumer or appliance is consuming water but rather may beattributed to the pressure difference in the water system on either sideof the consumer or appliance.

A substantial plateau in a pattern of water usage may constitute asequence of signals indicative of water consumption of uniform flow ratethat occurs following a spike in flow rate that occurs at the start ofthe same pattern. Such a plateau may represent the actual flow rate thatthe consumer or appliance is consuming water. A remedial action mayinclude recording in memory usage information attributable to waterappliance usage. The first water event may be associated with a firstwater appliance and the second water event may be associated with asecond water appliance. The at least one processor may be configured toidentify a first water appliance associated with the first water eventand a second water appliance associated with the second water event.

In some embodiments, the at least one processor may be configured toidentify a first water appliance associated with the first water eventbefore the use of a second appliance begins. Identification may beginbefore or after the usage begins. The at least one processor may beconfigured to differentiate between water events by identifyinginflexion locations in the at least one overall water usage indicator ofthe distributed water infrastructure. An inflexion point may be a firstderivative, or a second derivative.

In some embodiments, the at least one processor may be configured todifferentiate between water events by identifying at least twoinflection locations. The at least one processor may be configured todifferentiate between water events by identifying inflexion locationsand deconstructing overlapping events into subcomponents based on priorstored signatures of the subcomponents. Only the beginning of a waterusage profile might be used to identify a water event.

The signatures of the subcomponents may be the unique consumptionpatterns of the individual water consumers or appliances that areconnected to some distributed water infrastructure. Each signatureconstitutes a group of signals indicative of water usage in time and mayoccur simultaneously with other signatures to form an aggregated mixedsignal.

In some embodiments, the at least two inflection locations may bebetween periods of at least one of no consumption or substantiallyuniform consumption.

A system may differentiate between water events by identifyinginflection locations. A general process may include segmenting thesignals indicative of water usage into individual water events usinginflection locations, where the inflection points are either rapidincreases in the consumption rate or rapid decreases in the consumptionrate between periods of no consumption or uniform consumption.

Deconstructing mixed events into subcomponents refers to a process ofseparating multiple signals indicative of simultaneous water usage, frommore than one consumer or appliance, into groups of signals eachrepresenting the consumption of a single water consumer or applianceconnected to the distributed water infrastructure. The deconstruction ofthe mixed events may be carried out by a mathematical algorithm thatresamples the mixed signal to produce the individual signals.

FIG. 9 illustrates an exemplary method 900 for differentiating betweenoverlapping water events in a distributed water infrastructure includinga plurality of water appliances. The operations of method 900 discussedherein are intended to be illustrative. In some embodiments, method 900may be implemented with one or more additional operations not described,and/or without one or more of the operations discussed. Additionally,the order in which the operations of method 900 are illustrated in FIG.9 and described herein is not intended to be limiting.

In some embodiments, method 900 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all the operations of method 900 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more of the operations ofmethod 900.

In some embodiments, at operation 905, at least one processor may beconfigured to repeatedly measure at least one overall water usageindicator of the distributed water infrastructure, the at least onewater usage indicator including at least one of an overall flow rate andan overall flow volume in the distributed water infrastructure. Atoperation 910, at least one processor may be configured to detect, inthe repeated measurements, a first sustained increase. At operation 915,at least one processor may be configured to store in memory a firstindicator of the first sustained increase. At operation 920, at leastone processor may be configured to attribute in memory the firstsustained increase to a first water event in the distributed waterinfrastructure. At operation 925, at least one processor may beconfigured to, during the first sustained increase, detect in theoverall measurements a second sustained increase. At operation 930, atleast one processor may be configured to store in memory a secondindicator of the second sustained increase. At operation 935, at leastone processor may be configured to attribute, in memory, the secondsustained increase to a second water event in the distributed waterinfrastructure. At operation 940, at least one processor may beconfigured to detect, following initiation of the first sustainedincrease and the second sustained increase, in the repeatedmeasurements, a decrease in the overall water usage indicator. Atoperation 945, at least one processor may be configured to attribute tothe decrease a third indicator.

In some embodiments, at operation 950, at least one processor may beconfigured to compare the third indicator with at least one of the firstindicator and the second indicator stored in memory to determine asubstantial match and determine a cessation of at least one of the firstwater event and the second water event. The measurement of water usagemay be performed by any one of the systems described herein, and/or themeasure of water usage may be performed by a third-party water measuringdevice. The measurement of water usage may be performed by separatedevices distributed by distance, where the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor a parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits of event-basedleak detection systems and methods. A measurement of the number ofliters consumed as a function of time may be transformed into a waterusage pattern that has a particular fingerprint or water usage pattern.A water usage pattern may be determined by any method consistent withidentification herein, such as the non-limiting examples of: event-basedthreshold method, guided machine learning, or automatic machinelearning. Water usage pattern determination may be assisted by a neuralnetwork, where a system may progressively improve performance todetermine, identify, and compare water usage patterns by consideringexamples. In some embodiments, a neural network may be used withouttask-specific programming.

In some embodiments, differentiating between overlapping water events ina distributed water infrastructure including a plurality of waterappliances may be implemented by alternative methods of receiving waterinformation, and employing event-based leak detection systems andmethods to provide granularity of water usage to an end user.

FIG. 10a illustrates an exemplary water usage pattern over time, withflow rate on the y-axis and time on the x-axis. The exemplary waterusage pattern may comprise a spike 1010 in the flow rate at thebeginning. In other examples, there might not be spike at the beginningof a water usage pattern. A spike may be large, or may be a differentmagnitude such as spikes 1011 and 1012. The increase in the water flowrate may be characteristic of a type of water usage. After initiation ofwater usage, the flow rate may take a period of time to reach a steadystate of water flow.

The exemplary water usage pattern in FIG. 10a may comprise a steadystate flow rate 1020 during the exemplary pattern. In some embodiments,a steady state flow rate may be a different magnitude, such as steadystate flow rates 1021 and 1022. Steady state flow rate 1020 may have acertain level of noise associated with the water usage. The signal tonoise ratio may be indicative of a type of water usage. The entirety ofthe water usage may comprise at least one unique water usage identifierthat is used to determine a type of water usage event. The entirety ofthe water usage may comprise at least one weak water usage identifierthat is used to assist in determining a type of water usage event. Thecombination of several water usage identifiers may be used to identifyor guess a type of water usage event. A heuristic method that usessimple manually defined rules may be used to determine a type of waterusage event. A water usage pattern shown in FIG. 10a may be determinedby any method consistent with identification described herein, such asthe non-limiting examples of a threshold method, guided machinelearning, or automatic machine learning. Water usage patterndetermination may be assisted by a neural network, where a system mayprogressively improve performance to determine, identify, and comparewater usage patterns by considering examples. In some embodiments, aneural network may be used without task-specific programming.

FIG. 10b illustrates an exemplary water usage pattern over time, withflow rate on the y-axis and time on the x-axis. FIG. 10b shows exemplaryoverlapping water usage patterns, where water usage pattern 1030overlaps with water usage pattern 1040. As shown in FIG. 10b , in someembodiments, a water usage pattern 1030 may begin before water usagepattern 1040. A steady state flow rate (Δ₁) of water usage pattern 1030may be different than a steady state flow rate (Δ₂) of water usagepattern 1040. Either water usage pattern 1030 or water usage pattern1040 may end first. A sustained decrease in steady state flow rate (Δ₃)may match a first water usage pattern steady state flow rate (Δ₁) and bedifferent than a second steady state flow rate (Δ₂). In such anembodiment, where (Δ₃) equals (Δ₁), water usage pattern 1030 can bedetermined to have been terminated. Water usage pattern 1030 may bedifferentiated from water usage pattern 1040, by subtracting acontribution of water usage pattern 1040, e.g., second steady state flowrate (Δ₂), from the water usage pattern that begins at (Δ₁) and isassigned a water pattern 1030 during the time period between (Δ₁) and(Δ₃). Similarly, in some embodiments, water usage pattern 1040 may bedetermined by subtracting a contribution of water usage pattern 1030,e.g., first steady state flow rate (Δ₁), from the water usage patternthat begins at (Δ₂) and is assigned a water pattern 1040 for the periodthat follows (Δ₂).

FIG. 10c illustrates an exemplary water usage pattern over time, withflow rate on the y-axis and time on the x-axis. FIG. 10c shows exemplaryoverlapping water usage patterns, where water usage pattern 1050 may bea repeating water usage pattern, e.g., a washing machine, that overlapswith singular water usage pattern 1060. As shown in FIG. 10c , in someembodiments, a water usage pattern 1050 may begin before water usagepattern 1060. A repeating water usage pattern 1050 might be readilyidentified by a distinct repeating pattern. An overlapping water usagepattern 1060 might frustrate automatic or manual identification of waterusage patterns 1050 and 1060, as the method of identification may relyon easily identifiable repeating patterns. An aspect of the presentdisclosure may be directed to handling this problem.

For example, a steady state flow rate (Δ₁) of water usage pattern 1050may be different than a steady state flow rate (Δ₂) of water usagepattern 1060. Either water usage pattern 1050 or water usage pattern1060 may end first. A first water usage pattern's steady state flow rate(Δ₁) may be different than a second steady state flow rate (Δ₂). Asustained decrease in steady state flow rate (Δ₃) may match a firstwater usage pattern's steady state flow rate (Δ₁) and be different thana second steady state flow rate (Δ₂). In such an embodiment, where (Δ₃)equals (Δ₁), water usage pattern 1050 can be determined to have beenterminated. Water usage pattern 1050 may be differentiated from waterusage pattern 1060, by subtracting a contribution of water usage pattern1060, e.g., second steady state flow rate (Δ₂), from the water usagepattern that begins at (Δ₁) and is assigned a water pattern 1050 for thetime period between (Δ₁) and (Δ₃). Similarly, in some embodiments, waterusage pattern 1060 may be determined by subtracting a contribution ofwater usage pattern 1050, e.g., a first steady state flow rate (Δ₁),from the water usage pattern that begins at (Δ₂) and is assigned a waterpattern 1060 for the period that follows (Δ₂).

In some embodiments, a water usage pattern may be determined by one ormore processing devices. The one or more processing devices may includeone or more devices executing some or all of the operations of method900 in response to instructions stored electronically on an electronicstorage medium. The one or more processing devices may include one ormore devices configured through hardware, firmware, and/or software tobe specifically designed for execution of one or more of the operationsof a method, for example method 900.

In some embodiments, several indicators of the water usage pattern maybe used to identify a type of water usage. The duration of water usagepattern 1000 may increase. For example, a water usage patterncorresponding to handwashing does not have a pre-determined length oftime. The steady state flow rate may increase depending on the waterusage. For example, a water usage pattern corresponding to handwashingmay use a larger amount of water if both hot and cold water are used. Asanother example, a faucet may not be fully opened, such that a waterusage pattern may have a low steady state flow rate. If one water usageindicator changes, a single water usage indicator may be used toidentify a type of water usage. For example, if a duration of waterusage changes, a particular flow rate volume and/or the magnitude ofnoise for a water flow pattern may be used to identify a type of waterusage.

FIG. 10d-10f illustrates exemplary water usage patterns over time, withflow rate on the y-axis and time on the x-axis. FIG. 10g furtherillustrates an exemplary current water usage pattern over time, withflow rate on the y-axis and time on the x-axis, and may include severalwater usage events.

In some embodiments, a system may be continually measuring water usage,and all types of water usage may be eventually experienced andidentified. The types of water usage can be categorized and stored inmemory to be compared with and used at a later time.

Exemplary Embodiments of Unrecognized Liquid Events Triggering RemedialAction

An aspect of some embodiments may include detecting water events thattrigger remedial actions. These remedial actions may be automatic orrequire confirmation of an end user. As an alternative to using absolutethresholding, which may be less reliable for abnormal consumptiondetection, a potential benefit of some embodiments may be that exemplarysystems and methods of the present disclosure may learn patterns ofsystem behavior and store them as water events. When a water event isdetected that deviates from the normal patterns, the system mayrecognize the deviation as a likely abnormal consumption and initiateremedial action. If, for example, the duration of an otherwise normalevent exceeds a norm, an alert may be signaled (e.g., “Your shower at8:30 am today was longer than usual. Save water by taking shortershowers!”).

An aspect of some embodiments may include a detection system for adistributed water infrastructure, where the system may be configured toidentify abnormal water use from water usage patterns in the distributedwater infrastructure, the system comprising at least one processor. Atleast one processor may be configured to receive from at least onesensor associated with the distributed water infrastructure signalsindicative of water usage in the distributed water infrastructure. Atleast one processor may be configured to determine at least one detectedpattern of signals, access a database of a plurality of stored waterusage patterns, where each stored water usage pattern may be associatedwith at least one normal water usage pattern. A normal water usagepattern may be a pattern of consumption, constituting a sequence ofsignals over time indicative of water consumption, that originates fromand characterizes the use of a particular water consumer orwater-consuming appliance that may be connected to a distributed waterinfrastructure and therefore represents a typical usage of water in thatwater system.

In some embodiments, at least one processor may be configured to comparethe at least one determined pattern with at least some of the pluralityof stored water usage patterns. At least one processor may be configuredto determine, based on the comparison, that at least one determinedpattern substantially deviates from at least one corresponding storedwater usage pattern. At least one processor may be configured toinitiate a remedial action when a substantial deviation may bedetermined. A substantial deviation between two water usage patterns maybe a deviation measured using a quantitative distance measure thatexceeds a predefined limit. The distance measure may be any quantitativemeasure of dissimilarity and the limit of the acceptable deviation maybe defined as the variance or standard deviation of the distancesbetween acceptable water usage patterns, beyond which the deviation maybe considered substantial.

In some embodiments, the remedial action may include closing and openinga valve to send pulses of water to communicate that an abnormal amountof water has been consumed. An abnormal amount of water for aconsumption event may be a quantitative value defining a volume of waterthat is beyond the acceptable volume for a normal consumption event in adistributed water infrastructure. The acceptable volume of a normalconsumption event may be a fixed predetermined value or may be learnedover a learning period. Pulses of water may include the physicalstopping and starting the water flow from the point of view of theend-user of a water-consuming appliance connected to the distributedwater infrastructure. The pulses of water will cause the user toexperience an intermittent burst of water representing a physicalindication of an abnormal consumption event in the water infrastructure.

In some embodiments, the at least one processor may be configured todetermine based on the comparison, an identity of a water userassociated with the deviation. A water user may be an individual whoregularly consumes water in a distributed water infrastructure throughthe water-consuming appliances connected to that infrastructure.

To determine an identity, the processor associated with the distributedwater infrastructure may compare, either completely or partially, a newwater consumption pattern with an identified, stored, water consumptionpattern associated with an end-user. This may be done using aquantitative distance measure of similarity or dissimilarity todetermine if the usage originates from the same end-user.

In some embodiments, the remedial action may include sending a messageto a device of the water user. A device of a water user may be anelectronic computing device that has the ability to communicate over anetwork and can therefore send and receive electronic messages. Thisdevice may be a mobile phone, a wearable computer, a tablet computer, alaptop computer, a desktop computer, similar devices disclosed herein,or any other variation thereof.

Exemplary Embodiments of Water Use Signatures for Identifying Operationof Water Appliances

An aspect of the disclosure may be directed to providing water usesignatures for identifying the operation of water appliances. Apotential benefit of using a water sensor upstream of many waterappliances such as toilets, sinks, showers, and washing machines mayinclude the ability to distinguish and track the operation of individualappliances by storing unique water usage signatures for each appliance.Each appliance may have a unique signature that can be associated tothat specific appliance. This signature may indicate what appliance isbeing used. The signature may be based upon clustering, which may bedone to create a defined signature for that appliance.

An aspect of the disclosure may be directed to a system for trackingusage of a plurality of water appliances in a distributed waterinfrastructure. In some embodiments, tracking usage refers to theprocess of recording water usage of water appliances in a distributedwater infrastructure. Tracking usage may include measuring water usageflow and time to deliver a picture of how an appliance has used water,or in what ways a distributed water infrastructure has consumed water.

In some embodiments, the system may comprise at least one processor. Theat least one processor may be configured to receive, from a location inthe distributed water infrastructure upstream of the plurality of waterappliances, historical water usage measurements. The at least oneprocessor may be configured to receive historical water usagemeasurements from locations upstream of the measuring unit. In this way,any appliance downstream may be measured. Historical water usagemeasurements refer generally to acts of measuring and storing bothusage, flow, time, and water patterns over a period to achieve a uniquefingerprint of the water used. The at least one processor may beconfigured to determine from the historical water usage measurements atleast one unique water usage signature associated with each of theplurality of water appliances.

In some embodiments, the at least one processor may be configured tostore in memory at least one unique water usage signature for each ofthe plurality of appliances. The at least one processor may beconfigured to receive, from the location in the distributed water. Theat least one processor may be configured to determine from the currentwater usage measurements at least one current water usage signature. Theat least one processor may be configured to compare the current waterusage signature with at least one of the unique water usage signaturesstored in memory to determine a match. The at least one processor may beconfigured to compare the current water usage signature with at leastone of the unique water usage signatures stored in memory to determine amatch by taking the unique water signatures and comparing them,algorithmically, to similar patterns. The at least one processor may beconfigured to ascertain an identifier of a water appliance in currentuse, based on the signature match. The at least one processor may beconfigured to ascertain an identifier that indicates a positive matchbased upon patterns and grouping of stored data with measured signals.

In some embodiments, the at least one water usage signature may includean initial spike, followed by a plateau. Regardless of the reason forthe initial spike, in some embodiments an initial spike may be observedin the water flow rate when certain appliances are used. The magnitudeof the spike may depend on characteristics unique to specificdistributed water infrastructures, such as for example the distance ofthe measuring unit from the appliance in use, which may affect themagnitude of the spike. The magnitude of the spike may depend oncharacteristics specific to an appliance. For instance, the spike maydepend on the amount of water consumed by the device.

In some embodiments, the at least one processor may be configured, basedon an ascertained identifier of the water appliance in current use, torecord, over time, aggregated usage information for the appliance. Atleast one processor may be configured to store operational informationabout the continued use of the water appliance in current use.Operational information may be any information that defines theappliance. By way of non-limiting example, operational information mayinclude water flow, water usage, duration of consumption, time ofconsumption, and water patterns.

In some embodiments, it may be typical that water is consumed bymultiple appliances at one time. This system may be able to distinguishand track the operation of individual appliances by storing unique waterusage signatures for each appliance, and may also be able to distinguishbetween multiple water appliances used simultaneously. The at least oneprocessor may be configured to extract the current water usage signaturefrom current water usage measurements that reflect multiple waterappliances used simultaneously. The at least one processor may beconfigured to distinguish multiple water appliances used simultaneously,by marking an indicator when a sustained increase in water flow isobserved.

In some embodiments, the at least one processor may be configured todetermine from the historical water usage measurements a plurality ofunique water usage signatures for a single water appliance, where eachwater usage signature corresponds to a differing operating state of thesingle water appliance. The at least one processor may be configured todetermine who may be using each device based on assignments of uniquewater usage signatures. A personal identifier might not associated withunique water usage signatures, but the unique water usage signatures maystill be associated with an anonymous water consumer. The at least oneprocessor may be configured to determine an identity of a water consumerbefore, after, or during the use of the device.

In some embodiments, the at least one processor may be configured todetermine from the historical water usage measurements a plurality ofunique water usage signatures for a single water appliance, where eachwater usage signature corresponds to the single water applianceoperating substantially simultaneously with at least one other waterappliance in the distributed water infrastructure. The substantiallysimultaneous operation may operate in rapid succession or within acertain time window, such as the non-limiting example of hands beingwashed after flushing a toilet.

In some embodiments, same model water appliances in the distributedwater infrastructure may share similar signatures, where the at leastone processor may be configured to use the similar signatures toaggregate water usage information by the model of the water appliance.The at least one processor may be configured to initiate a waterpreservation action based at least in part on the current usagesignature, and in some embodiments, a water preservation action may bean action that can be automatic, semi-automatic, or a recommendation onhow to use the appliance in a more efficient manner. The action may alsobe to notify the end-user of the imminent failure of the appliance. Atleast one processor may be configured to initiate a water preservationaction using an identifier and stored operational information.

In some embodiments, the at least one processor may be configured toreceive from a user, an identification of a water appliance in currentuse, and to associate in memory the identification with the currentwater usage signature. The at least one processor may be configured todetermine an identity of water usage appliances by accessing signatureinformation from an external source. The external source may includeinformation provided by an appliance manufacturer. The external sourcemay include a database of appliances and associated water usagesignatures. The processor may be configured to store in memoryinformation obtained from the external source. The water preservationaction may include reporting, to an administrator, the identifier andwater usage data.

In some embodiments, the water preservation action may include providingsuggestions to a water administrator for reducing water consumption.Suggestions provided by the system may include suggestions to better usethe appliance in an efficient cost-effective manner. Different waterreduction strategies may be suggested based on the identified appliancesused in the distributed water infrastructure.

In some embodiments, the water preservation action may include causingthe display of a comparison of current water usage information withhistorical water use information for an appliance. The at least oneprocessor may be configured to determine, based on the water usagesignature of the appliance in current use, an abnormality in operationof the appliance in current use, and to send an alert on theabnormality. The identifier may include a type and brand of anappliance. The identifier may include at least one of a floor and roomlocation of the water appliance in current use. The at least oneprocessor may be configured to output cumulative water consumption datafor each identified appliance in the distributed water infrastructure.

FIG. 11 illustrates an exemplary method 1100 for tracking usage of aplurality of water appliances in a distributed water infrastructure. Theoperations of method 1100 discussed herein are intended to beillustrative. In some embodiments, method 1100 may be implemented withone or more additional operations not described, and/or without one ormore of the operations discussed. The order in which the operations ofmethod 1100 are illustrated in FIG. 11 and described herein is notintended to be limiting. Additionally, the steps may be performedcontemporaneously, or with some delay, with the measurement of waterusage. The measurement of water usage may be performed by any one of thesystems described herein. The measurement of water usage may beperformed by separate components distributed by distance, and theoperations may be performed immediately or at a later time via bathprocessing or delayed processing.

In some embodiments, method 1100 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all the operations of method 1100 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or softwarespecifically designed for execution of one or more of the operations ofmethod 1100.

In some embodiments, at operation 1110, at least one processor may beconfigured to receive, from a location in the distributed waterinfrastructure upstream of the plurality of water appliances, historicalwater usage measurements. At operation 1120, at least one processor maybe configured to determine from the historical water usage measurementsat least one unique water usage signature associated with each of theplurality of water appliances. Water usage signatures may include aninitial spike, followed by a plateau, as demonstrated in FIGS. 10a-g .At operation 1130, at least one processor may be configured to store inmemory the unique water usage signature for each of the plurality ofappliances.

In some embodiments, at operation 1140, at least one processor may beconfigured to receive, from the location in the distributed waterinfrastructure upstream of the plurality of water appliances, currentwater usage measurements. At operation 1150, at least one processor maybe configured to determine from the current water usage measurements atleast one current water usage signature. At operation 1160, at least oneprocessor may be configured to compare the current water usage signaturewith at least one of the unique water usage signatures stored in memoryto determine a match.

In some embodiments, at operation 1170, at least one processor may beconfigured to, based on the signature match, ascertain an identifier ofa water appliance in current use. The match may be used to aggregateusage information for the appliance over time.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, where the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processors using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits of event-basedleak detection systems and methods. A measurement of the number ofliters consumed as a function of time may be transformed into a waterusage pattern that has a particular fingerprint or water usage pattern.A water usage pattern may be determined by any method consistent withidentification herein, such as the non-limiting examples of: event-basedthreshold method, guided machine learning, or automatic machinelearning. Determining water usage pattern may be done with theassistance of a neural network, where a system may progressively improveperformance to determine, identify, and compare water usage patterns byconsidering examples. In some embodiments, a neural network may be usedwithout task-specific programming.

In various alternative methods, tracking usage of a plurality of waterappliances in a distributed water infrastructure may be implemented byalternative methods of receiving water information, and employingevent-based leak detection systems and methods to provide granularity ofwater usage to an end user.

Exemplary Embodiments of a Noise Generator Used to Identify an Appliance

An aspect of some embodiments may include providing for noise generatorsto identify specific appliances. In order to aid in identifying waterappliances, a potential benefit of some embodiments may includeproviding noise generators associated with specific water appliances.When the appliances are in use, each noise generator may send a uniquenoise signal to a receiver, which may identify the appliance in use. Inthis way, water usage measurements may be reliably associated with aparticular appliance. An aspect of the disclosure may be directed to asystem for tracking usage of a plurality of water appliances in adistributed water infrastructure, the system comprising at least oneprocessor. At least one processor may be configured to receive, from alocation in the distributed water infrastructure upstream of theplurality of water appliances, water usage information from one of theplurality of water appliances. At least one processor may be configuredto receive a noise signal unique to the water appliance. At least oneprocessor may be configured to correlate the water usage information ofthe water appliance with the unique noise signal of the appliance toidentify water usage of the appliance.

In some embodiments, the noise signal may be generated via operation ofthe appliance. The noise signal may be generated by an aftermarket noisegenerator associated with the water appliance in the distributed waterinfrastructure.

Exemplary Embodiments of an all-in-One Learning Water Usage TrackingSystem

An aspect of some embodiments may include providing for all-in-onelearning water usage tracking systems. A potential benefit of someembodiments may include offering a plug and play unit that incorporatesflow and volume measurement, a communication module, a learningalgorithm, and an electronic valve. With such an installation, a usermay install a single device and track water usage throughout adistributed water system.

An aspect of some embodiments include a centralized system for trackingwater usage of a plurality of water appliances in a distributed waterinfrastructure. The system an electronically controllable valve havingan inlet for flow connection to a source of water and an outlet for flowconnection to the distributed water infrastructure. The system maycomprise a water flow sensor associated with the valve.

In some embodiments, the system may comprise a water volume sensorassociated with the valve. The water volume sensor may be the samesensor as the water flow sensor. For example, a sensor capable ofdetecting the flow rate of water may also be able to integrate the flowrate over a period of time to determine the volume of water that hasflowed past the sensor.

In some embodiments, the system may comprise a receiver, a transmitter,and at least one processor. The at least one processor may be configuredto collect from the water flow sensor and the water volume sensor, flowand volume information relating to the upstream plurality of waterappliances. The at least one processor may be configured to execute alearning algorithm to learn and log normal events in the distributedwater infrastructure. The at least one processor may be configured tocompare, in real time, current sensed events with learned normal events.The at least one processor may be configured to initiate remedial actionif an event sensed in real time deviates from a learned normal event,where the remedial action may include sending a notification via thetransmitter. The at least one processor may be configured to command toclose the valve in response to a close valve instruction received viathe receiver.

In some embodiments, the remedial action may include generatingcompliance data. The remedial action may include supplying thecompliance data to an insurance company.

Exemplary Embodiments of Changing Zero Identifying Abnormal Consumption

Systems and methods of the present disclosure may provide the ability tolearn normal system behavior and establish a baseline for overall systemwater usage when the water system is in a sleep state (nights and onweekends, for example). The system may track sleep state water usageover time, and if an upward trend is detected, signal a leak.

An aspect of some embodiments may include a system for changing theprotection level for detection of abnormal consumption in a distributedwater infrastructure by sensing the activity of the liquidinfrastructure, the system comprising at least one processor. Theprocessor may be configured to receive, from a liquid sensor upstream ofa plurality of liquid appliances in the distributed liquidinfrastructure, overall liquid consumption measurements. The processormay determine periods when the distributed liquid infrastructure is inan inactive state of substantial non-use of liquid appliances, trackliquid consumption during a plurality of times when the distributedliquid infrastructure is in an inactive state, detect an upward trend inliquid consumption over the plurality of times, and initiate remedialaction when the upward trend is detected.

In some embodiments, a high-sensitivity detector may be employed todifferentiate between water usage and detect low level leaks. A changein the baseline during water use may indicate an abnormal water event. Arising flow rate during water use may indicate an abnormal water event.

In some embodiments, the remedial action may include generating anabnormal consumption alert. An increase in water consumption betweensequential times of non-use may be insufficient to cause an initiationof remedial action.

Exemplary Embodiments of Aggregating Demographic Data with Water Meters

A potential benefit of some embodiments may include aggregatingdemographic data with water sensors. In some embodiments, systems andmethods of the present disclosure may identify if a particular applianceis malfunctioning. As described above and below, water appliances mayhave their own water sensor for detecting malfunctions. Alternatively, asingle sensor on the distributed water infrastructure may be able todetermine, from water usage profiles, whether many water appliances aremalfunctioning. If so, various forms of remedial action may beautomatically taken. Systems may aggregate data from smart water sensorsacross many properties to identify trends in water usage by categoriesof appliances. Those trends may then be used for benchmarking purposes.

An aspect of some embodiments may include a system for determiningoperational states of specific categories of water appliances using aplurality of geographically distributed water sensors. In someembodiments, the system may comprise at least one processor. The systemmay comprise at least one central processor, which may aggregate datafrom multiple smart water sensors. The processor may perform processingsteps in a distributed network.

In some embodiments, at least one processor may be configured to receivewater appliance usage data from the plurality of geographicallydistributed water sensors, where each water sensor may be locatedupstream of a plurality of water appliances in an associated distributedwater infrastructure. Each water sensor may be configured to collectdata from an infrastructure inlet flow reflective of operation of atleast one specific category of water appliance downstream of the watersensor. At least one processor may be configured to compare the waterappliance usage data to determine trends in operation of the at leastone specific category of water appliance across a population.

In some embodiments, at least one processor may be configured to outputinformation about trends in usage data. The geographically distributedwater sensors may be each associated with a differing household and mayeach include a transmitter for sending water appliance usage informationfor processing by the at least one central processor. The specificcategory of water appliance may include at least one category chosenfrom the group comprising washing machines, dishwashers, toilets,specific models of washing machines, specific models of dishwashers, andspecific models of toilets, and the information about trends in usagemay include at least one of malfunctions, efficiency, volume of waterused, water flow rate, time of day of usage, location of usage, andcycles run in a specific time period. The at least one central processormay be configured to alert an administrator of a particular distributedwater infrastructure if water usage for a category of appliance deviatessubstantially from a threshold. The at least one central processor maybe configured to alert a water appliance manufacturer when a trendrelating to malfunctions is detected.

In some embodiments, the geographically disbursed water sensors may beeach associated with at least one local processor that may be configuredto determine from collected data water usage, patterns sufficient toidentify operation of specific appliances within an associateddistributed water infrastructure. The local processor may transmit, forprocessing by the at least one central processor, information about theoperation of the identified specific appliances. The collected data fromthe infrastructure inlet flow may include substantially all water flowthrough the infrastructure inlet, and the at least one central processormay be configured to determine geographical trends in home and away timeperiods based on the collected data. The specific appliances may includewater faucets, shower heads, and toilets, where the at least one oflocal processor and the at least one central processor may be configuredto determine home and away time from data reflective of at least one ofwater faucet usage, shower head usage, and toilet usage.

In some embodiments, the at least one local processor may be configuredto receive, from at least one sensor associated with the distributedwater infrastructure, signals indicative of water usage in thedistributed water infrastructure and generate, from the signalsindicative of water usage, at least one water usage signature. The localprocessor may compare the at least one water usage signature with atleast one of the unique water usage signatures stored in memory todetermine a match, based on the signature match, and ascertain anidentifier of a specific water appliance corresponding to the waterusage signature. The local processor may transmit, for processing by theat least one central processor, operational information about thespecific water appliance.

An aspect of some embodiments may include methods for determiningoperational states of specific categories of water appliances using aplurality of geographically distributed water sensors. The method maycomprise receiving water appliance usage data from the plurality ofgeographically distributed water sensors, where each water sensor may belocated upstream of a plurality of water appliances in an associateddistributed water infrastructure. Each water sensor may be configured tocollect from an infrastructure inlet flow, via at least one localprocessor, data reflective on operation of at least one specificcategory of water appliance downstream of the water sensor. The methodmay comprise comparing, via at least one central processor, the waterappliance usage data to determine trends on the operation of the atleast one specific category of water appliance across a population.

In some embodiments, the method may comprise outputting informationabout usage trends. The method may comprise transmitting water applianceusage information from the geographically distributed water sensors, andreceiving water appliance usage information via the at least one centralprocessor. The geographically distributed water sensors may each beassociated with a differing household and each geographicallydistributed water sensor may include a transmitter.

In some embodiments, the specific category of water appliance mayinclude at least one category chosen from the group comprising washingmachines, dishwashers, toilets, specific models of washing machines,specific models of dishwashers, and specific models of toilets, and theinformation about trends in usage may include at least one ofmalfunctions, efficiency, volume of water used, water flow rate, time ofday of usage, location of usage, and cycles run in a specific timeperiod. The method may comprise alerting an administrator of aparticular distributed water infrastructure if water usage for acategory of appliance deviates substantially from a threshold. Themethod may comprise alerting a water appliance manufacturer when a trendrelating to malfunctions is detected.

In some embodiments, a method may comprise determining, via the at leastone central processor, from collected data water usage, patternssufficient to identify operation of specific appliances within anassociated distributed water infrastructure, and transmittinginformation about the operation of the identified specific appliances.The method may comprise determining, via the at least one centralprocessor, geographical trends in home and away time periods based onthe collected data, where the collected data from the infrastructureinlet flow may include substantially all water flow through theinfrastructure inlet. The method may comprise determining, via at leastone of the at least one local processor and the at least one centralprocessor, home and away time from data reflective of at least one ofwater faucet usage, shower head usage, and toilet usage.

In some embodiments, a method may comprise receiving, via at least onelocal processor, from at least one sensor associated with thedistributed water infrastructure, signals indicative of water usage inthe distributed water infrastructure. The method may comprisegenerating, via at least one local processor, from the signalsindicative of water usage, at least one water usage signature, andcomparing, via at least one local processor, the at least one waterusage signature with at least one of the unique water usage signaturesstored in memory to determine a match. Based on the signature match, themethod may include ascertaining, via at least one local processor, anidentifier of a specific water appliance corresponding to the waterusage signature, and transmitting, via at least one local processor, forprocessing by the at least one central processor, operationalinformation about the specific water appliance.

FIG. 12a illustrates an exemplary method 1200 for determiningoperational states of specific categories of water appliances using aplurality of geographically distributed water sensors. The operations ofmethod 1200 discussed herein are intended to be illustrative. In someembodiments, method 1200 may be implemented with one or more additionaloperations not described, and/or without one or more of the operationsdiscussed. Additionally, the order in which the operations of method1200 are illustrated in FIG. 12 and described herein is not intended tobe limiting.

In some embodiments, at operation 1210, at least one processor may beconfigured to receive water appliance usage data from the plurality ofgeographically distributed water sensors, where each water sensor may belocated upstream of a plurality of water appliances in an associateddistributed water infrastructure. Each water sensor may be configured tocollect data from an infrastructure inlet flow reflective on theoperation of at least one specific category of water appliancedownstream of the water sensor. At least one processor may be configuredto collect data from an infrastructure inlet flow reflective of theoperation of the at least one specific category of water usage.

In some embodiments, at operation 1220, at least one processor may beconfigured to compare the water appliance usage data from the pluralityof geographically distributed water sensors to determine trends inoperation of the at least one specific category of water applianceacross a population. At operation 1230, at least one processor may beconfigured to output information about the trends in operation.

In some embodiments, method 1200 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all the operations of method 1200 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more operations of method1200.

FIG. 12b illustrates an exemplary system 1240 for determiningoperational states of specific categories of water appliances using aplurality of geographically distributed water sensors. In someembodiments, a sensor may be a “flowless” sensor configured as a flowsensor. FIG. 12b shows a plurality of sensors that communicate through acommunication channel to a server. The plurality of sensors may beconnected to the server with wired and/or wireless communicationcomponents. The server may be a server based in a cloud. The server maybe accessed by a variety of devices including mobile devices and desktopcomputers.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, where the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits of event-basedleak detection systems and methods. A measurement of the number ofliters consumed as a function of time may be transformed into a waterusage pattern that has a particular fingerprint or water usage pattern.A water usage pattern may be determined by any method consistent withidentification herein, such as the non-limiting examples of: event-basedthreshold method, guided machine learning, or automatic machinelearning. Determining water usage patterns may be assisted using aneural network, where a system may progressively improve performance todetermine, identify, and compare water usage patterns by consideringexamples. A neural network may be used without task-specificprogramming.

In various alternative embodiments, determining operational states ofspecific categories of water appliances using a plurality ofgeographically distributed water sensors may be implemented usingmethods for receiving water information and employing event-based leakdetection systems and methods to provide granularity of water usage toan end user.

Exemplary Embodiments of Water Profiles to Detect Malfunctioning WaterAppliances

An aspect of some embodiments may include a system for determining, froma location upstream of a plurality of water appliances, whether aspecific water appliance may be malfunctioning. A location upstream maybe any point in the distributed water infrastructure before the pointwhere a water consumer is located. A location downstream may be anylocation in the distributed water infrastructure after the point where asensing device is located. The information gathered from this locationmay be used in processes to determine the consumption of water passingthrough. The information gathered from this location may indicate that aspecific water appliance is malfunctioning. A specific water appliancemalfunction may an appliance that is broken and/or working outside ofcorrect specifications. A specific water appliance malfunction may notnecessarily mean that a water appliance shows a current problem, rather,it may mean a problem may be imminent.

In some embodiments, a system according to the present disclosure mayinclude at least one processor. At least one processor may be configuredto detect, from at least one sensor in a distributed waterinfrastructure upstream of the plurality of water appliances, aplurality of normal water usage profiles. Normal water usage profilesmay be patterns that are gathered over time showing the normal usage ofa water appliance. Normal water usage of an appliance may include anyinformation that represents the proper working of the appliance.Information that represents a proper working of an appliance may beappliance specific and the information may include a normal water usageprofile.

In some embodiments, at least one processor may be configured toassociate at least one of the plurality of normal water usage profileswith each of the plurality of water appliances. The at least oneprocessor may be configured to store each of the plurality of normalwater usage profiles in a manner that associates each of the pluralityof normal water usage profiles with its corresponding water appliance.At least one processor may be configured to detect at least one currentwater usage profile. The at least one processor may be configured todetect a profile by continually comparing measured current water usageprofiles against a stored database of normal water usage profiles.Current water usage profiles may be generated in a like manner to normalwater usage profiles except that they are temporary.

In some embodiments, at least one processor may be configured to comparethe at least one current water usage profile with at least one of thestored normal water usage profiles to determine a corresponding identityof an associated water usage appliance and to determine if a substantialdeviation exists between the stored normal water usage profile for theidentified appliance and the at least one current water usage profile.The substantial deviation may be reflective of a potential malfunctionin the associated water usage appliance.

Determining a corresponding identity refers to the process of matching awater appliance against a set of stored patterns and characteristicsthat identify a particular water appliance. An associated water usageappliance may be any similar water appliance stored in a data retrievalsystem that has a specific set of characteristics that can be used tohelp identify the matching water system. A substantial deviation may beany deviation from what an appliance with a specific water usage profileis expected to be and what the system may be seeing currently. Basedupon a magnitude of this difference (deviation), the difference mightmean that the water appliance is not working properly.

In some embodiments, at least one processor may be configured toinitiate remedial action if the substantial deviation, reflective of apotential malfunction, is determined. Initiating remedial action may beanything from a self-test to a service call or probe by other sensingsystems. A service call may be an actual repair or preventative action.A recommendation to purchase a new appliance may include times when thesystem determines that based upon the deviation, the best and cheapestcourse of action would be to purchase a new appliance. If this is thecase, the system may inform why this decision was made and may suggestappropriate models to buy. Such a recommendation may be based on thespecific water appliance.

In some embodiments, the at least one processor may be configured toreceive aggregate signals reflective of simultaneous operation ofmultiple water appliances and to extract from the aggregate signalsnormal water usage profiles for specific appliances. In one embodiment,this may be part of a system for determining, from a location upstreamof a plurality of water appliances, whether a specific water applianceis malfunctioning. The system may comprise at least one processorconfigured to: detect, from the at least one sensor in a distributedwater infrastructure upstream of the plurality of water appliances, aplurality of normal water usage profiles, associate each normal waterusage profile with a specific water usage appliance, and store eachnormal water usage profile for each specific water usage appliance. Thesystem may detect at least one current water usage profile, compare theat least one current water usage profile with at least one of the storednormal water usage profiles to determine a corresponding identity of anassociated water usage appliance and to determine if a substantialdeviation exists between the normal water usage profile for theidentified appliance and the current water usage profile. The system mayinitiate remedial action if the substantial deviation exists.

In some embodiments, at least one processor may be configured todetermine water usage spikes in the aggregate signals, and to identifyan initiation of use of a water appliance based on a determined waterusage spike. The identified appliance may include a water pump, wherethe substantial deviation is reflective of a pump malfunction. The atleast one processor may be configured to detect a pump malfunctionbefore a failure, where the remedial action may include transmitting amessage indicating an expected failure. The identified appliance may bea toilet where the substantial deviation is reflective of a toilet valveleak.

In some embodiments, the at least one processor may be configured toreceive from a user an indication of an appliance location in thedistributed water infrastructure, and to store the location in a mannerassociating the location with the corresponding water appliance. Aremedial action may be initiated if the at least one processordetermines that the current water usage profile indicates a flow rate ofgreater than 50-100 ml in less than 0.18 seconds. The at least oneprocessor may be configured to determine the corresponding identity of awater appliance based on at least one of initial rise in flow rate,average sustained flow rate, noise in a flow rate, and duration of waterconsumption.

In some embodiments, the identified appliance may be determined to bemalfunctioning based on at least one characteristic not used to identifythe water appliance. The at least one processor may be configured toidentify a malfunction based on a change in acoustic noise in the atleast one current water usage profile.

In some embodiments, a remedial action may include providing informationabout the malfunction for transmission to a manufacturer of an appliancedetermined to be malfunctioning. The remedial action may include sendinga notification to initiate a service call. The at least one processormay be configured to provide an estimate of at least one of wasted waterand cost for continuing to operate a faulty device. The at least oneprocessor may be configured to output for display, analytics on theidentified appliance, where the analytics may be based on historicaldata captured over time for the identified appliance. At least oneprocessor may be configured to output to a display a visual comparisonof current usage of an appliance and normal appliance usage. Theremedial action may include providing a recommendation to purchase a newappliance.

In some embodiments, determining if a substantial deviation exists mayinclude accessing a database of profiles of malfunctions, anddetermining that a match exists between the current water usage profileand one or more profiles of malfunctions.

An aspect of some embodiments may include systems for determining, froma location upstream of a plurality of water appliances, whether aspecific water appliance is malfunctioning. The system may comprisememory for storing at least one preloaded characteristic associated withnormal operation of the specific water appliance. The system maycomprise at least one processor, which may be configured to detect atleast one current water usage profile associated with the specific waterappliance. At least one processor may be configured to compare the atleast one current water usage profile with at least one preloadedcharacteristic to determine if the at least one current water usageprofile is reflective of a malfunction. At least one processor may beconfigured to initiate remedial action if the at least one current waterusage profile is reflective of a malfunction.

In some embodiments, the at least one current water usage profile mayinclude a plurality of overlapping normal water usage profiles, and theat least one processor may be configured to segregate, from theplurality of overlapping normal water usage profiles, the at least onecurrent water usage profile associated with the specific waterappliance.

FIG. 13 illustrates an exemplary method 1300 for determining, from alocation upstream of a plurality of water appliances, whether a specificwater appliance may be malfunctioning. The operations of method 1300discussed herein are intended to be illustrative. In some embodiments,method 1300 may be implemented with one or more additional operationsnot described, and/or without one or more of the operations discussed.Additionally, the order in which the operations of method 1300 areillustrated in FIG. 13 and described herein is not intended to belimiting.

In some embodiments, method 1300 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all the operations of method 1300 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or softwarespecifically designed for execution of one or more of the operations ofmethod 1300.

In some embodiments, at operation 1310, at least one processor may beconfigured to detect, from at least one sensor in a distributed waterinfrastructure upstream of the plurality of water appliances, aplurality of normal water usage profiles. At operation 1320, at leastone processor may be configured to associate at least one of theplurality of normal water usage profiles with each of the plurality ofwater appliances. At operation 1330, at least one processor may beconfigured to store each of the plurality of normal water usage profilesin a manner associating each of the plurality of normal water usageprofiles with an associated water appliance. At operation 1340, at leastone processor may be configured to detect at least one current waterusage profile.

In some embodiments, at operation 1350, at least one processor may beconfigured to compare the at least one current water usage profile withat least one of the stored normal water usage profiles to determine acorresponding identity of an associated water usage appliance and todetermine if a substantial deviation exists between the stored normalwater usage profile for the identified appliance and the at least onecurrent water usage profile, where the substantial deviation may bereflective of a potential malfunction in the associated water usageappliance. At least one processor may be configured to determine thecorresponding identity of a water appliance based on at least one ofinitial rise in flow rate, average sustained flow rate, noise in a flowrate, and a duration of water consumption

In some embodiments, determining may refer to a process of matching awater appliance against a set of stored patterns and characteristicsthat identify the particular water appliance. In some embodiments,matching may be performed by a machine learning algorithm. The matchingmay be performed automatically, after the at least one processor hasbeen provided a training set. At operation 1360, at least one processormay be configured to initiate remedial action if the substantialdeviation, reflective of a potential malfunction, is determined.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, where the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits of event-basedleak detection systems and methods. A measurement of the number ofliters consumed as a function of time may be transformed into a waterusage pattern that has a particular fingerprint or water usage pattern.A water usage pattern may be determined by any method consistent withidentification herein, such as the non-limiting examples of: event-basedthreshold method, guided machine learning, or automatic machinelearning. Water usage pattern determination may be assisted by a neuralnetwork, where a system may progressively improve performance todetermine, identify, and compare water usage patterns by consideringexamples. A neural network may be used without task-specificprogramming.

In various alternative methods, determining, from a location upstream ofa plurality of water appliances, whether a specific water appliance maybe malfunctioning may be implemented by alternative processes forreceiving water information, and employing event-based leak detectionsystems and methods to provide granularity of water usage to an enduser.

Exemplary Embodiments of Graphical Interfaces Enabling CategoryComparison of Water Usage Over Time

An aspect of some embodiments may provide for a graphical user interface(GUI) for enabling category comparison of water usage over time. Whilewater users are able to compare their water bills from month to month totrack overall water usage, a potential benefit of some embodiments maybe that systems and methods of the present disclosure may compare waterusage across time periods on a category basis (e.g., irrigation, coolingtower, water appliances, etc.). Such a benefit can provide greatergranular detail on how consumers are using their water, and provideinsight on how to reduce consumption. A potential benefit of someembodiments of the present disclosure may include transforming signalsinto a display output in a readily readable way.

An aspect of some embodiments may include a system for tracking, in adistributed water infrastructure, water usage by category. Tracking adistributed water system may include the process of identifying thecharacteristic consumption of all of the water consumed in a distributedwater infrastructure in real-time or in near-real-time. Characteristicconsumption may include a particular water-consuming appliance or deviceworking automatically, being used in a standard way by an individual, orbeing used to perform a particular task by an individual in a way thatmay be unique to that individual. The tracking process may also includemonitoring volume, flow rate, duration, and other quantitative featuresof water consumption based on these, to provide a detailed view of thenature of the water consumption.

In some embodiments, the system may comprise at least one processor. Atleast one processor may be configured to receive from at least onesensor associated with the distributed water infrastructure signalsindicative of water usage in the distributed water infrastructure.

In some embodiments, at least one processor may be configured toreceive, from at least one sensor associated with the distributed waterinfrastructure, signals indicative of water usage in the distributedwater infrastructure. The processor may be configured to construct,based on the signals indicative of water usage, a plurality of profiles.Constructing a plurality of profiles may include the process ofsegmenting the signals indicative of water usage into groups of signals,each of which represents a particular use of a particularwater-consuming device or appliance that may be connected to thedistributed water infrastructure, where each of these groups of signalsmay be a water event profile. These profiles may be extracted by meansof an automatic, semi-automatic, or manual segmentation algorithm.

In some embodiments, at least one processor may be configured to assigneach profile to one of a plurality of water usage categories. At leastone processor may be configured to collect from the at least one sensor,signals indicative of water usage for substantially all water deliveredthrough the distributed water infrastructure in a time period. At leastone processor may be configured to construct a plurality of water usageprofiles, in the aggregate encompassing substantially all waterdelivered through the distributed water infrastructure in the timeperiod. Substantially all water delivered refers to the sensor beingable to sense a sufficient amount of water consumption in somedistributed water infrastructure so that the water consumption trackingmay be performed to substantial completion on all of the water passingthrough the distributed water infrastructure.

In some embodiments, at least one processor may be configured to assigneach constructed water usage profile to one of the plurality of waterusage categories. Assigning may include the process of mapping each ofthe water event profiles extracted from the water consumption signal toone or only one of the categories of water usage that has beenidentified for the distributed water infrastructure. The mapping processmay be automatic, semi-automatic, or manual. An automatic orsemi-automatic mapping process may include using a mathematical modelbased on a supervised or semi-supervised machine learning algorithm thatis applied to the extracted profiles to categorize them.

In some embodiments, at least one processor may be configured to output,for display, water usage for the time period, for each of the pluralityof water usage categories. The at least one processor may be configuredto display to an administrator, in graphical form, comparativeinformation over time for a specific category. Graphical forms mayinclude using appropriate graphs to present the extracted data for eachcategory of water consumption so that it is clear and informative. Thismay include collective graphical presentation of all the time-basedsignals for each profile for a category of water consumption.Comparative information may include the graphical presentation of eachof the categories of water consumption in such a way that it illustratesthe changes in water usage for that particular water consumptioncategory over some period of time and allows the user to compare theconsumption for that category from different time periods.

In some embodiments, the plurality of water usage categories may includeat least one of toilets, sinks, urinals, showers, washing machines,dishwashers, ice makers, irrigation, subcategories of processingmachines, and uncategorized water usage. The plurality of water usagecategories each may include an identity of an individual. The signalsindicative of water usage may be sufficiently granular so as to capturewater usage patterns that tend to be unique to particular individuals,where each water usage pattern associated with a particular individualmay be assigned to separate categories for the particular individual.

In some embodiments, the at least one processor may be configured tooutput, for display to an administrator in graphical form, comparativewater usage information between categories. The at least one processormay be configured to identify consumption by a particular type ofwater-consuming appliance in a distributed water infrastructure inreal-time, and to assign to separate types of categories water usageinformation associated with the particular type of water-consumingappliance. The at least one processor may be configured to track atleast one of the volume, flow rate, and duration of water consumption,by category. The plurality of water usage profiles may be extracted fromthe signals indicative of water usage using a segmentation algorithm.The at least one sensor may include a flow meter having a resolution ofat least 0.2 liters per hour.

In some embodiments, the processor may be configured to receive arequest for a report of water usage for at least one category during asub-time period less than the duration of the time period, where the atleast one processor may be configured to output water usage informationfor the sub-time period.

An aspect of some embodiments may include computer-implemented methodsfor monitoring water usage in a distributed water infrastructure. Insome embodiments, the method may comprise tracking historical waterusage information using at least one sensor upstream of a plurality ofwater appliances in the distributed water infrastructure. The method maycomprise determining from the historical water usage informationreceived by the at least one sensor, a plurality of normal waterprofiles for each of the plurality of water appliances in thedistributed water infrastructure. The method may comprise categorizingthe plurality of normal water profiles into at least one of twocategories, including water appliance type and individual users, andoutputting, for display by category, water usage information

In some embodiments, the method may comprise outputting informationdisplaying an amount of water usage for at least one category of waterusage. Outputting may include providing graphical information fordisplaying an amount of water usage over time. Outputting by at leastone category may include providing aggregated information about allwater used by a particular individual within a time period. Outputtingby at least one category may include providing aggregated informationabout all water used by a particular category of water appliance withina time period.

In some embodiments, a method may further comprise the steps ofreceiving current water usage information from the at least one sensor,determining a current water profile, categorizing the current waterprofile into at least one category of water usage, and outputting datafor generating a categorized report of a current total amount of waterconsumed. The method may further comprise the step of displaying a trendin water usage for at least one water usage category.

In some embodiments, the method may further comprise the step ofproviding an estimate for water usage for at least one water usagecategory. The plurality of water usage categories may include at leastone of toilets, sinks, urinals, showers, washing machines, dishwashers,ice makers, irrigation, subcategories of processing machines, anduncategorized water usage. The plurality of water usage categories mayeach include an identity of an individual.

FIG. 14 illustrates an exemplary method 1400 for tracking, in adistributed water infrastructure, water usage by category. Theoperations of method 1400 discussed herein are intended to beillustrative. In some embodiments, method 1400 may be implemented withone or more additional operations not described, and/or without one ormore of the operations discussed. Additionally, the order in which theoperations of method 1400 are illustrated in FIG. 14 and describedherein is not intended to be limiting.

In some embodiments, method 1400 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all the operations of method 1400 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more of the operations ofmethod 1400.

In some embodiments, at operation 1410, at least one processor may beconfigured to receive, from at least one sensor associated with thedistributed water infrastructure, signals indicative of water usage inthe distributed water infrastructure. At operation 1420, at least oneprocessor may be configured to, based on the signals indicative of waterusage, construct a plurality of profiles. At operation 1430, at leastone processor may be configured to assign each profile to one of aplurality of water usage categories. At operation 1440, at least oneprocessor may be configured to collect, from the at least one sensor,signals indicative of water usage for substantially all water deliveredthrough the distributed water infrastructure in a time period. Atoperation 1450, at least one processor may be configured to construct aplurality of water usage profiles, which may in the aggregate encompasssubstantially all water delivered through the distributed waterinfrastructure in the time period. At operation 1460, at least oneprocessor may be configured to assign each constructed water usageprofile to one of the plurality of water usage categories.

In some embodiments, at operation 1470, at least one processor may beconfigured to output, for display, water usage for the time period, foreach of the plurality of water usage categories. The measurement ofwater usage may be performed by any one of the systems described herein,and/or the measure of water usage may be performed by a third-partywater measuring device. The measurement of water usage may be performedby separate devices distributed by distance, where the processingoperations may be performed locally or at a central location. Theprocessing operations may be performed in real time, and/or at a latertime. The processing operations may also be provided by distributedparallel or cloud computing infrastructures with data and resultstransported to the cloud or parallel processor using wireless or wirednetworks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits of event-basedleak detection systems and methods. In some embodiments, measurement ofthe number of liters consumed as a function of time may be transformedinto a water usage pattern that has a particular fingerprint or waterusage pattern. A water usage pattern may be determined by any methodconsistent with identification herein, such as the non-limiting examplesof: event-based threshold method, guided machine learning, or automaticmachine learning. Water usage pattern determination may be assisted by aneural network, where a system may progressively improve performance todetermine, identify, and compare water usage patterns by consideringexamples. A neural network may be used without task-specificprogramming.

In various alternative methods, tracking water usage by category may beimplemented by alternative methods of receiving water information, andemploying event-based leak detection systems and methods to providegranularity of water usage to an end user.

Exemplary Embodiments of Differentiating Between Individuals

An aspect of some embodiments may include developing systems and methodsto differentiate between particular water appliances being used. Aspectsof the present disclosure may also enable differentiation between usersof the appliances, based on specific water usage behavior of the users.This, for example, may allow the system to identify who in a home takesthe longest showers or leaves the bathroom sink running the longest.

An aspect of some embodiments may include systems for differentiatingbetween water usage of multiple water consumers using a commondistributed water infrastructure. In some embodiments, the system maycomprise at least one processor. The at least one processor may beconfigured to receive, from a water sensor in the distributed waterinfrastructure upstream of a plurality of appliances, signals indicativeof water usage.

In some embodiments, at least one processor may be configured toconstruct from the signals indicative of water usage a plurality ofwater event profile signatures. At least one processor may be configuredto, based on differences between similar water event profiles, associateat least one water event profile signature with a first water consumerand associate a second water event profile signature with a second waterconsumer. Differences between similar water event profiles may refer toa delta that can be discerned between similar water events. Thesedifferences may be analyzed and stored. The process of learning thesedifferences may use algorithms that learn from and make predictionsbased on the data available (e.g., genetic algorithms and randomdecision forest algorithms).

In some embodiments, at least one processor may be configured to storethe water event profile signatures for the first water consumer and thesecond water consumer. The process of constructing ongoing water eventprofiles may refer to when a system according to an embodiment of thepresent invention creates baseline water event profiles and analyzes awater event. A water event profile may be refined successively over timeand with more data.

In some embodiments, at least one processor may be configured toconstruct current water event profiles reflecting subsequent water usagein the distributed water infrastructure. At least one processor may beconfigured to compare the current water event profiles with water eventprofile signatures stored in memory. At least one processor may beconfigured to, based on the comparison, attribute a first current waterevent profile to the first water consumer and attribute a second currentwater event profile to the second water consumer.

At least one processor may output data for generating at least onereport of water usage by the first water consumer. A report may be anyinformation that is transmitted, regardless of means of transmission, toanother party or parties informing them of a water event and/or waterusage. A report may also include detailed water event profileinformation.

In some embodiments, at least one processor may be further configured toassociate at least one water event profile with at least one appliance,where the output data segregates water usage of the at least oneappliance by the first water consumer. The at least one processor may beconfigured to update the water event profile signatures using thecurrent water event profiles. Each water event profile signature mayhave a form substantially similar to a form of a water event profile.Each water event profile signature may reflect characteristics of acorresponding water event profile.

In some embodiments, the at least one processor may be configured toreceive an input on the identity of the first water consumer, and tostore in memory, in association with a first water event profilesignature, the identity of the first water consumer. The at least oneprocessor may be configured to recognize the first water consumer fromthe second water consumer based on distinct usage patterns within anassociated current water event profile. Each water usage profilesignature may take into account at least one of duration of water usage,time of water usage, volume of water usage, and rate of water usage.

In some embodiments, each water usage profile signature may take intoaccount at least two of a duration of water usage, a time of waterusage, a volume of water usage, and a rate of water usage. In someembodiments, a system may further comprise associating a first group ofthe plurality of water event profile signatures with the first waterconsumer and associating a second group of the plurality of water eventprofile signatures with the second water consumer, where at least someof the first group of the plurality of water event profile signaturesmay be each associated with differing water appliances.

In some embodiments, the differing water appliances may include at leastone faucet, where the at least one processor may be configured to usethe water event profile signatures to distinguish between usage of theat least one faucet by the first water consumer and the second waterconsumer. The at least one processor may be configured to permit a waterevent profile signature to be assigned to an individual through a userinput. The at least one processor may be configured to permit a waterevent profile to be assigned to an individual through a learningalgorithm. The at least one processor may be configured to receivetraining data on a typical consumer to improve identification of a firstwater consumer.

At least one report of water usage may include an amount of water aspecific individual consumed using specific appliances. The at least oneprocessor may be configured to send a notification to an end userrequesting user input on water consumption not associated withparticular water consumers. The at least one processor may be configuredto estimate when particular water consumers may be away for a period oftime, by comparing current water usage profiles with water usage profilesignatures, and noting that, during the period of time, current waterusage profiles do not correspond to any water usage profile signatures.

In some embodiments, the at least one processor may be configured toinitiate a remedial action if a current water event profile associatedwith the first water consumer substantially deviates from an associatedwater event profile signature for the first water consumer. The liquidconsumer may be a specific individual. The liquid consumer may be aspecific appliance. In some embodiments, the water consumer may be atype of appliance.

The at least one processor may be configured to permit a water eventprofile to be assigned to an individual through a user input. The atleast one processor may be configured to permit a water event profile tobe assigned to an unidentified individual through a learning algorithm.

An aspect of some embodiments may include methods for differentiatingbetween water usage of multiple water consumers using a commondistributed water infrastructure. The method may comprise receiving froma water sensor, associated with the distributed water infrastructure andupstream of a plurality of appliances, signals indicative of waterusage.

In some embodiments, the method may comprise constructing from thesignals indicative of water usage a plurality of water event profilesignatures. The method may comprise associating at least one water eventprofile signature with a first water consumer and associating a secondwater event profile signature with a second water consumer. The methodmay comprise storing the water event profile signatures for the firstwater consumer and the second water consumer. The method may compriseconstructing current water event profiles reflecting subsequent waterusage in the distributed water infrastructure, and comparing the currentwater event profiles with water event profile signatures stored inmemory. The method may comprise, based on the comparison, attributing afirst current water event profile with the first water consumer andattributing a second current water event profile to the second waterconsumer.

In some embodiments, the method may comprise outputting data forgenerating at least one report of water usage by the first waterconsumer. The method may further comprise updating the water eventprofile signatures using the current water event profiles.

FIG. 15 illustrates an exemplary method 1500 for differentiating betweenwater usage of multiple water consumers using a common distributed waterinfrastructure. The operations of method 1500 discussed herein areintended to be illustrative. In some embodiments, method 1500 may beimplemented with one or more additional operations not described, and/orwithout one or more of the operations discussed. Additionally, the orderin which the operations of method 1500 are illustrated in FIG. 15 anddescribed herein is not intended to be limiting.

In some embodiments, method 1500 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all the operations of method 1500 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more of the operations ofmethod 1500.

In some embodiments, at operation 1510, at least one processor may beconfigured to receive, from a water sensor in the distributed waterinfrastructure upstream of a plurality of appliances, signals indicativeof water usage. At operation 1520, at least one processor may beconfigured to construct, from the signals indicative of water usage, aplurality of water event profile signatures. At operation 1530, at leastone processor may be configured to, based on differences between similarwater event profiles, associate at least one water event profilesignature with a first water consumer and associate a second water eventprofile signature with a second water consumer. At operation 1540, atleast one processor may be configured to store the water event profilesignatures for the first water consumer and the second water consumer.At operation 1550, at least one processor may be configured to constructcurrent water event profiles reflecting subsequent water usage in thedistributed water infrastructure. At operation 1560, at least oneprocessor may be configured to compare the current water event profileswith water event profile signatures stored in memory. At operation 1570,at least one processor may be configured to, based on the comparison,attribute a first current water event profile to the first waterconsumer and attribute a second current water event profile to thesecond water consumer. At operation 1580, at least one processor may beconfigured to output data for generating at least one report of waterusage by the first water consumer.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, where the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits of event-basedleak detection systems and methods. A measurement of the number ofliters consumed as a function of time may be transformed into a waterusage pattern that has a particular fingerprint or water usage pattern.A water usage pattern may be determined by any method consistent withidentification herein, such as the non-limiting examples of: event-basedthreshold method, guided machine learning, or automatic machinelearning. Water usage pattern determination may be assisted by a neuralnetwork, where a system may progressively improve performance todetermine, identify, and compare water usage patterns by consideringexamples. A neural network may be used without task-specificprogramming.

In various alternative methods, differentiating between water usage ofmultiple water consumers using a common distributed water infrastructuremay be implemented by alternative methods of receiving waterinformation, and employing event-based leak detection systems andmethods to provide granularity of water usage to an end user.

Exemplary Embodiments of a Time-Based System for Detecting Water UsageAbnormalities

Aspects of some embodiments may provide for time-based schemes fordetecting water usage abnormalities. In some embodiments, remedialactions may vary depending on time of day or day of week. That is, sincewater usage profiles may vary depending on time and day, normal activitymay necessarily vary over time. By taking these variations into account,a potential benefit of some embodiments may be greater accuracy.

An aspect of some embodiments may include a system for detectingabnormal liquid usage over time in a distributed liquid infrastructure,the system comprising at least one processor. At least one processor maybe configured to receive, from at least one sensor associated with thedistributed liquid infrastructure, signals indicative of water usage. Atleast one processor may be configured to determine from the signals aplurality of baseline time-based water usage profiles, such that thetime-based water usages profiles vary from each other depending on time.At least one processor may be configured to receive from the at leastone sensor signals indicative of current water usage. At least oneprocessor may be configured to, determine from the current signals acurrent water usage profile associated with at least one of a particularday of week and a particular time of day of the current signals. Atleast one processor may be configured to compare the current water usageprofile with at least some of the baseline water usage profilescorresponding to at least one of the particular day of week and time ofday.

In some embodiments, at least one processor may be configured todetermine a likely water usage abnormality based on the comparison. Theat least one processor may be configured to initiate remedial action ifan abnormality is determined.

In some embodiments, the water usage profiles may vary from each otherbased on a schedule. The water usage profiles may vary from each otherbased on at least one of day of week and time of day. The at least oneprocessor may be configured to permit an administrator to set at leastone of the baseline water usage profiles for a futureadministrator-selected time period, where the at least one processor maybe configured to automatically set a baseline water usage profile basedon at least one of time and day.

In some embodiments, remedial action may include automatically closing avalve. The remedial action may include sending a warning. The remedialaction may include a user alert configured to only be sent duringscheduled hours.

Exemplary Embodiments of Varying Water Usage Costs Based on Appliance

A potential benefit of some embodiments may be that systems and methodsof the present disclosure may provide infrastructure and/or methods forcharging different rates per appliances. For example, by using a singlemeter and/or sensor a service provider may charge differently for aconsumer's home and garden usage. Applying variable prices may includeapplying incremental water prices.

Historically, water prices usually have been proportional to the volumeof water consumed by the end user. In some embodiments, each unit ofvolume may cost a certain amount of money (e.g., $4 per 1000 liter, $1per 1000 gallons, $350 k per 1 acre-foot, etc.). Prices for the firstfixed volume of water and another price for other different fixedvolumes are shown by way of non-limiting example in TABLE 1 below:

TABLE 1 From (liters) To (liters) Price ($) per liter 1 500 4 501 1200 61201 N/A 11

In some embodiments, different prices may also be associated to the typeof customer, such as the following non-limiting examples: residential,commercial, and senior citizens. A potential benefit of some embodimentsmay providing different prices according to the types of consumption, sospecific usage may have a different price although the water may be thesame water. This way a regulator may set a low price for essentialconsumption, such as drinking, and higher prices for luxury usage, suchas irrigating a garden or filling up a swimming pool.

An aspect of some embodiments may include an electronic sensing andallocation system for a distributed water infrastructure containing aplurality of differing appliances. The system may comprise at least oneprocessor. The at least one processor may be configured to receive, fromat least one sensor upstream of the plurality of differing appliances, aplurality of signals indicative of water usage within the distributedwater infrastructure. The at least one processor may be configured toextract, from the plurality of signals, first information identifying avolume of water usage of at least a first appliance. The at least oneprocessor may be configured to attribute a first volume of water to afirst category. At least one processor may be configured to extract,from the plurality of signals, second information identifying a volumeof water usage of at least a second appliance. The at least oneprocessor may be configured to attribute a second volume of water to asecond category, where a first rate schedule may be applicable to thefirst category, and a second rate schedule, other than the first rateschedule, may be applicable to the second category,

In some embodiments, at least one processor may be configured to outputa first indication of the first volume of water together with anindicator attributing the first volume of water to the first rateschedule. The at least one processor may be configured to output asecond indication of the second volume of water together with anindicator attributing the second volume of water to the second rateschedule. This may enable billing the first and second volumes of waterto a consumer at differing rates based on differing uses.

An aspect of the disclosure may be directed to a system for applyingvariable prices in a distributed water infrastructure based water usageby a plurality of differing appliances, the system comprising at leastone processor. The at least one processor may be configured to receive,from a meter upstream of the plurality differing appliances, a signalindicative of water usage. The at least one processor may differentiatebetween water usage of a first appliance and a second appliance,attribute a first volume of water usage to the first appliance,attribute a second volume of water usage to the second appliance, billat a first rate water usage attributed to the first appliance, and billat a second rate water usage attributed to the second appliance.

In some embodiments, the first indication of the first volume of watermay include a category indication. The output indicator of at least thefirst volume of water further may include an indication of a time periodin which the first volume of water was consumed. The output indicator ofat least the first volume of water may contain at least one applianceindicator that attributes the first volume of water to at least oneappliance that consumed the first volume of water. The categoryindication may reflect at least one of outdoor irrigation use and indooruse.

In some embodiments, the at least one processor may be configured todistinguish between water used for personal hygiene and water used bywater-consuming machines, and to attribute water usage to acorresponding category.

In some embodiments, the at least a first appliance may include waterappliances used in an irrigation system, where the first volume of watermay be output for billing according to an irrigation rate schedule. Atleast one of a first rate schedule and a second rate schedule may takeinto account a time period of water usage, where volumes of water may beoutput together with a time period indicator to enable billing, at leastin part, on the time period of water usage. The time period indicatormay be reflective of water usage during a drought condition, to enableapplication of a drought billing rate. The at least one processor may beconfigured to output a suggestion to a user to alter water usagepractice in order to obtain lower water rates.

In some embodiments, a method may further comprise a transmitter, wherethe at least one processor may be configured to transmit, via thetransmitter, the indicator attributing the first volume of water to thefirst rate schedule and the second indicator attributing the secondvolume of water to the second rate schedule to a central billing server.The at least one processor may be configured to incrementally time stampcontinuing water usage to enable variable billing rates based ontime-based consumption. The at least one processor may be configured toidentify a plurality of differing appliances of a same type, and toattribute the plurality of differing appliances to a common category.The first appliance may be at least one of a toilet, faucet, and shower.

The at least one processor may be configured to initiate a remedialaction when a total cost of water consumption reaches a preset thresholdvalue. The remedial action may include causing an alert message to besent, sending a signal to a valve to stop water flow, and providing anotification regarding consumer compliance with a water restriction.

In some embodiments, at least one sensor may be a flow sensor. The atleast one sensor may be a smart meter configured to record consumptionof water in intervals of an hour or less and to communicate consumptionof water to a water utility company.

FIG. 16 illustrates an exemplary method 1600 for electronic sensing andallocation for a distributed water infrastructure containing a pluralityof differing appliances. The operations of method 1600 discussed hereinare intended to be illustrative. In some embodiments, method 1600 may beimplemented with one or more additional operations not described, and/orwithout one or more of the operations discussed. Additionally, the orderin which the operations of method 1600 are illustrated in FIG. 16 anddescribed herein is not intended to be limiting.

In some embodiments, method 1600 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all the operations of method 1600 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more of the operations ofmethod 1600.

In some embodiments, at operation 1610, at least one processor may beconfigured to receive, from at least one sensor upstream of theplurality of differing appliances, a plurality of signals indicative ofwater usage within the distributed water infrastructure. At operation1620, at least one processor may be configured to extract, from theplurality of signals, first information identifying a volume of waterusage of at least a first appliance. At operation 1630, at least oneprocessor may be configured to attribute a first volume of water to afirst category. At operation 1640, at least one processor may beconfigured to extract, from the plurality of signals, second informationidentifying a volume of water usage of at least a second appliance. Atoperation 1650, at least one processor may be configured to attribute asecond volume of water to a second category, where a first rate schedulemay be applicable to the first category and a second rate schedule,other than the first rate schedule, may be applicable to the secondcategory. At operation 1660, at least one processor may be configured tooutput a first indication of the first volume of water together with anindicator attributing the first volume of water to the first rateschedule. At operation 1670, at least one processor may be configured tooutput a second indication of the second volume of water together withan indicator attributing the second volume of water to the second rateschedule. This may enable billing of the first and second volumes ofwater to a consumer at differing rates based on differing uses.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, where the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide novel benefits in event-based leak detectionsystems and methods. A measurement of the number of liters consumed as afunction of time may be transformed into a water usage pattern that hasa particular fingerprint or water usage pattern. A water usage patternmay be determined by any method consistent with identification herein,such as the non-limiting examples of: event-based threshold method,guided machine learning, or automatic machine learning. Water usagepattern determination may be assisted by a neural network, where asystem may progressively improve performance to determine, identify, andcompare water usage patterns by considering examples. A neural networkmay be used without task-specific programming.

In various alternative methods, electronic sensing and allocation for adistributed water infrastructure containing a plurality of differingappliances may be implemented by alternative methods of receiving waterinformation, and employing event-based leak detection systems andmethods to provide granularity of water usage to an end user.

Exemplary Embodiments of a White List for Abnormal Water Events

A dictionary of profiles may be used to identify an abnormal waterusage. When detecting such profiles, the system may identify the waterflow as an abnormal consumption or a faulty appliance. Additionally, thesystem may store water profiles that would otherwise be classified asabnormal water events, except that they are whitelisted. For example, asystem may attempt to characterize an event from prior characteristics,and if it cannot find a prior characteristic the system may prompt theuser to do either add the water event to a whitelist or to a list ofknown abnormal water events.

In some embodiments, the system may comprise at least one processor. Thesystem may comprise memory for storing a plurality of abnormal waterusage profiles. The at least one processor may be configured to receivefrom a water meter in a distributed water infrastructure successiveindications of water usage. At least one processor may be configured tocompare the successive indications of water usage with the storedabnormal water usage profiles. At least one processor may be configuredto determine, based on the comparison, a correlation between at leastone indication and at least one abnormal water usage profile. At leastone processor may be configured to initiate remedial action when acorrelation is determined.

An aspect of some embodiments may include a system for detectingabnormal water consumption, the system may comprise memory for storing aplurality of abnormal water usage profiles and at least one processorconfigured to receive from a water meter in a distributed waterinfrastructure successive indications of water usage. The system maycompare the successive indications of water usage with the storedabnormal water usage profiles, and based on the comparison, determine acorrelation between at least one indication and at least one abnormalwater usage profile. When a correlation is determined, the system mayinitiate remedial action.

Exemplary Embodiments of a Learning Algorithm and Learning Period

An aspect of some embodiments may include a system for recognizingliquid usage patterns in a distributed liquid infrastructure. In someembodiments, the system may be configured to classify normal or abnormalwater (or fluid) usage and may take action based on a comparison with aclassification database. The system may comprise at least one processor.At least one processor may be configured to receive, from at least onesensor, information about liquid usage in the distributed liquidinfrastructure. At least one processor may be configured to determineover time expected patterns of liquid usage and classify the expectedpatterns as normal usage patterns. At least one processor may beconfigured to detect a usage pattern that does not correspond to aclassified normal usage pattern and initiate remedial action when theusage pattern does not correspond to a classified normal usage pattern.

In some embodiments, at least one processor may be configured to measurewater usage patterns during a learning period and execute a learningalgorithm. A learning algorithm may include steps for a length of time,or the number of events required, before the learning algorithmcompletes. A learning algorithm may include steps for prompting an enduser to classify a water usage, prompting an end user to initiate awater usage, and classifying the water usage.

In some embodiments, the learning algorithm may determineclassifications for the water usage patterns automatically. The learningalgorithm may learn to identify events without knowing what the eventis. For example, the learning algorithm may identify a normal waterusage that occurs every morning, and classify the event as normal evenif the learning algorithm does not identify the event as a shower.

An aspect of the disclosure may be directed to a system for recognizingliquid usage patterns in a distributed liquid infrastructure, the systemcomprising at least one processor. The processor may be configured toreceive from at least one sensor, information about liquid usage in thedistributed liquid infrastructure. The processor may determine over timeexpected patterns of liquid usage, classifying the expected patterns asnormal usage patterns. The processor may detect a usage pattern thatdoes not correspond to a classified normal usage pattern, and initiateremedial action when a usage pattern is detected that does notcorrespond to a classified normal usage pattern.

Exemplary Embodiments of Cloud-Based Water Analytics

An aspect of some embodiments may include a system for monitoring waterusage of a plurality of appliances in a plurality of distributedlocations remote from one another. A system may comprise manydistributed water meters (from any vendor) connected to the cloud. Thesystem may learn normal water profiles, transfer data to a waterdata-analytics system in the cloud that processes the data, and provideuseful information. The system may monitor distributed water devices andsensors that can be located at various locations. Even though thesedevices are not necessarily in close proximity, such devices may senddata to a central location, and may interact with each other via thesystem.

In some embodiments, the system may comprise at least one processor. Thesystem may comprise at least one central processor. A central processormay be a processor that is configured to receive information and performprocessing steps from several disparate locations.

In some embodiments, at least one processor may be configured to receivewater usage data from the plurality of distributed locations. At leastone processor may be configured to determine, from the water usage datareceived from the plurality of distributed locations, a common applianceused in each of the plurality of distributed locations. A commonappliance may include an appliance, or class of appliances, that atleast two different distributed water infrastructures share in common. Acommon appliance might not be an identical appliance, but rather a typeor model of appliance that makes it possible to compare appliances indifferent distributed water infrastructures.

In some embodiments, at least one processor may be configured to analyzea subset of the water usage data attributable to the common appliance todetermine usage patterns associated with the common appliance across theplurality of distributed locations. Aggregating may include toaggregating all the relevant water data from the devices into onecentral database for comparison and analytics. Information about usageof the common appliance may include to information gathered andaggregated to provide insight into the proper working of other commonappliances located in other locations.

In some embodiments, at least one processor may be configured to outputusage pattern analytics associated with the common appliance. The atleast one central processor may be configured to receive water usagedata from a plurality of local processors at the plurality ofdistributed locations, where the plurality of local processors may beconfigured to analyze local patterns of water usage, match a localpattern of water usage with a pattern associated with the commonappliance, and transmit to the at least one central processor waterusage data associated with the common appliance.

In some embodiments, the at least one central processor may beconfigured to transmit, to a plurality of local processors at each ofthe plurality of distributed locations, at least one water usage patternsignature to facilitate detection of the common appliance by theplurality of local processors. The at least one central processor may beconfigured to determine, from the water usage data, whether a commonappliance may be malfunctioning at one of the plurality of distributedlocations.

In some embodiments, the at least one central processor may beconfigured to store an address associated with an administrator of eachof the plurality of distributed locations and to send an alert to theadministrator of a malfunctioning appliance. The at least one centralprocessor may be configured to determine, using the water usage data, atleast one analytic relating to at least one of frequency of use of anappliance and duration of use of an appliance. The at least one centralprocessor may output the at least one analytic for presentation to amanufacturer of the appliance. The at least one central processor may beconfigured to aggregate, in memory, historical water consumptioninformation about the common appliance, gleaned from water usage datacollected over a plurality of days. The historical consumptioninformation may include at least one of a water flow profile, water flowrate, water pressure, and total water consumed for a cycle or period.

In some embodiments, the at least one central processor may beconfigured to receive water usage data from the plurality of localprocessors on at least a daily basis. The at least one central processormay be configured to identify a malfunction by comparing current waterusage data at a first location with water usage data for an applianceknown to have malfunctioned at a second location. The at least onecentral processor may be configured to output, for each of the pluralityof distributed locations, a comparison of local water usage withaggregated communal water consumption. The at least one centralprocessor may be configured to output, for each of the plurality ofdistributed locations, usage pattern analytics categorizing local waterusage by appliance.

In some embodiments, each local processor may be associated with atleast one local flow sensor upstream of a plurality of appliances andconfigured to collected data relating to simultaneous operation of atleast some of the plurality of appliances. The at least one centralprocessor may be configured to receive water usage information derivedfrom the data relating to simultaneous operation of at least some of theplurality of appliances. The at least one local flow sensor may have aresolution of at least 0.2 liters per hour.

An aspect of the disclosure may be directed to a system for monitoringwater usage of a plurality of appliances in a plurality of distributedlocations remote from one another, the system comprising at least oneprocessor. The at least one processor may be configured to receive waterusage data from the plurality of distributed locations, and analyze thewater usage data to determine usage patterns in the usage data from eachof the plurality of locations. The at least one processor may determine,in each of the usage patterns, a common appliance used in each of theplurality of distributed locations, and aggregate, from the water usagedata, information about usage of the common appliance from the pluralityof locations.

FIG. 17 illustrates an exemplary method 1700 for monitoring water usageof a plurality of appliances in a plurality of distributed locationsremote from one another. The operations of method 1700 discussed hereinare intended to be illustrative. In some embodiments, method 1700 may beimplemented with one or more additional operations not described, and/orwithout one or more of the operations discussed. Additionally, the orderin which the operations of method 1700 are illustrated in FIG. 17 anddescribed herein is not intended to be limiting.

In some embodiments, method 1700 may be implemented in one or moreprocessing devices. The one or more processing devices may include oneor more devices executing some or all the operations of method 1700 inresponse to instructions stored electronically on an electronic storagemedium. The one or more processing devices may include one or moredevices configured through hardware, firmware, and/or software to bespecifically designed for execution of one or more of the operations ofmethod 1700.

In some embodiments, at operation 1710, at least one processor may beconfigured to receive water usage data from a plurality of distributedlocations. At operation 1720, at least one processor may be configuredto determine from the water usage data received, from the plurality ofdistributed locations, a common appliance used in each of the pluralityof distributed locations.

In some embodiments, at operation 1730, at least one processor may beconfigured to analyze a subset of the water usage data attributable tothe common appliance to determine usage patterns associated with thecommon appliance across the plurality of distributed locations. Atoperation 1740, at least one processor may be configured to output usagepattern analytics associated with the common appliance.

In some embodiments, the measurement of water usage may be performed byany one of the systems described herein, and/or the measure of waterusage may be performed by a third-party water measuring device. Themeasurement of water usage may be performed by separate devicesdistributed by distance, where the processing operations may beperformed locally or at a central location. The processing operationsmay be performed in real time, and/or at a later time. The processingoperations may also be provided by distributed parallel or cloudcomputing infrastructures with data and results transported to the cloudor parallel processor using wireless or wired networks.

In accordance with the present disclosure, some of the embodimentsdescribed herein provide examples of the novel benefits of event-basedleak detection systems and methods. A measurement of the number ofliters consumed as a function of time may be transformed into a waterusage pattern that has a particular fingerprint or water usage pattern.A water usage pattern may be determined by any method consistent withidentification herein, such as the non-limiting examples of: event-basedthreshold method, guided machine learning, or automatic machinelearning. Water usage pattern determination may be assisted by a neuralnetwork, where a system may progressively improve performance todetermine, identify, and compare water usage patterns by consideringexamples. A neural network may be used without task-specificprogramming.

In various alternative methods, monitoring water usage of a plurality ofappliances in a plurality of distributed locations may be implemented byalternative methods of receiving water information, and employingevent-based leak detection systems and methods to provide granularity ofwater usage to an end user.

Exemplary Embodiments of Increasing the ‘Zero’ Threshold

The minimum flow rate for consumption may be increased to the level of areported abnormal water flow having a certain flow rate, when theadministrator chooses to ignore the abnormality. This may avoidreporting the same flow as an abnormal consumption more than once.

An aspect of the disclosure may be directed to a system for detectingabnormal water consumption. The system may comprise at least oneprocessor. The at least one processor may be configured to receive fromat least one sensor a water usage indicator, determine an existence of alikely abnormality from the received indicator, report the likelyabnormality to an administrator, receive from the administrator amessage to ignore the likely abnormality, adjust a threshold to preventfurther reporting to the administrator when the water usage indicatorcorresponding to the likely abnormality is later detected again. Inorder to prevent customer harassment and over-messaging, the system mayhave a mechanism to adjust a threshold to reduce further reporting tothe administrator.

An aspect of some embodiments may include a system for detectingabnormal water consumption, the system comprising at least oneprocessor. The at least one processor may be configured to receive fromat least one sensor a water usage indicator, determine an existence of alikely abnormality from the received indicator, report the likelyabnormality to an administrator, receive from the administrator amessage to ignore the likely abnormality, adjust a threshold to preventfurther reporting to the administrator when the water usage indicatorcorresponding to the likely abnormality may be later detected again.

FIG. 18 illustrates an exemplary graphical user interface 1800 for asystem that may remotely control a valve and track water usage. Thegraphical user interface may provide system controls to a user, indicatewhether a valve status is open or closed, and provide options to open orclose the valve. The graphical user interface may show a system state,and may indicate whether there is a leak detected in the system, whethera specific valve is opened or closed, a vacation status of an end user,a status of the monitoring system (e.g., normal or threshold), and adetection mode status (e.g., adaptive or manual). The graphical userinterface may also provide information on monthly consumption and weeklyconsumption.

FIG. 19a illustrates an exemplary system 1900 for detecting consumptionof liquids and/or water quality. System 1900 may include a server 1902and clients, such as client 1907. Client 1907 may communicate withserver 1902 on a cloud 1901. Communication between a server and aparticular client 1907 may take place through a cellular provider 1904,or through a gateway 1905. Communication with an end user may take placethrough a smart phone application 1903. Client 1907 may be installedwith a distributed water infrastructure 100, downstream of a waterprovider main meter 1906. Client 1907 may be part of a system comprisinga dry segment 1908 and a wet segment 1909. Client 1907 may comprise acontrol panel 1910, antenna 1911, GSM modem 1912, processor 1913, powermodule 1914, battery 1915, NVM-nonvolatile memory 1916, magnetic hallsensor 1917, magnetic hall sensor reader 1918, sensors 1919, diaphragmvalve 1920, flow meter 1921, and unmeasured flow reducer (UFR) 1922.

FIG. 19b illustrates an exemplary system 1930 for detecting consumptionof liquids and/or water quality. In some embodiments, a system may beconfigured to perform data processing and storage operations in thecloud. System 1930 may include a system 1931 that may comprise aprocessor 1932. Processor 1932 may be a CPU configured to transfer rawor unprocessed data to the cloud. System 1930 may include a valve 1933,a flow sensor 1934, and a battery 1935. In some embodiments, system 1930may comprise water quality sensors 1937. Processor 1932 may beconfigured to transfer data to the cloud via a cellular modem 1936 thatmay establish a cellular link to the cloud. The cloud may comprise adistributed network of servers, with at least one data processing unit1938 and with at least one component for data storage 1940. Data storedin the cloud may be accessed from remote locations through a Web GUI1939.

FIG. 19c illustrates an exemplary system 1950 for detecting consumptionof liquids and/or water quality. In some embodiments, a system may beconfigured such that an end device provides data collection and datacommunication. Such a system may be configured to perform additionaldata processing steps and data storage in the cloud. System 1950 mayinclude an end point device 1951 that may comprise a processor 1952.Processor 1952 may be a CPU configured to transfer raw or unprocesseddata to the cloud through a communication link. System 1950 may includea valve 1954, a flow sensor 1955, a certified meter 1956, and waterquality sensors 1957. Processor 1952 may be configured to transfer datato the cloud via a communication unit 1953, which may establish acellular link to the cloud. The cloud may comprise a distributed networkof servers, with at least one data processing unit 1958 and at least onecomponent for data storage 1960. Data stored in the cloud may beaccessed from remote locations through a web GUI 1959.

The foregoing concepts though described in connection with water are notlimited to water, and can be used with any fluid, such as chemicals,petroleum products, waste products, gaseous/liquid substances, or anyother material used in a commercial or non-commercial application. Inaddition, while the preceding concepts are expressed for exemplarypurposes in a single form, it may be envisioned that each concept couldbe expressed in terms of either a system, method, or computer readablemedium. In such instances, the claim elements are expressible as steps,instructions, or hardware. Although the invention has been described ina variety of embodiments, this description is not meant to be construedin a limiting manner. Inventive concepts may include systems thatfeature combinations of elements and/or processing steps from eachdisclosed embodiment. Various modifications of the disclosed embodimentsas well as alternative embodiments of the inventions are expresslyenvisioned by this disclosure.

For example, in one exemplary embodiment, systems consistent with thepresent invention may comprise an electronically controllable valve, aremote communication transmitter, a remote communication receiver, atleast one consumption sensor for measuring water flow informationassociated with the distributed water infrastructure, and at least oneprocessor. The system may comprise at least one central processor. Thesystem may further comprise any of the components from exemplary systems200, 201, 400, 401, 1800, and 1900, and user interface 1240.

The system may be configured to detect a leak, and inform waterconsumers about their water consumption. The system may comprisespecific elements to measure the status of water, process thisinformation, communicate to an end user, and take an automatic remedialaction. The system may receive from at least one sensor associated withthe distributed water infrastructure signals indicative of water usagein the distributed water infrastructure, and aggregate groups of signalsto construct a plurality of time-based water event profiles, each waterevent profile containing a distribution of water usage indicators overtime. The system may store a subset of the plurality of water eventprofiles in memory as normal water event profiles, and receive, from theat least one sensor, signals indicative of current water usage in thedistributed water infrastructure. The system may construct, from thesignals indicative of current water usage, at least one current waterevent profile, and compare the at least one current water event profilewith normal water event profiles stored in the memory. The system mayinitiate remedial action if the at least one current water event profiledoes not substantially correspond to normal water event profiles storedin the memory.

The system may further determine, from the water flow informationobtained from the at least one consumption sensor, a potential abnormalconsumption associated with the distributed water infrastructure. Thesystem may automatically close a valve, without human intervention, whenthe potential abnormal consumption is determined. The system maytransmit, via the remote communication transmitter to a remoteadministrator, alert information about the potential abnormalconsumption to enable an administrator to decide based on thetransmitted information whether to reopen the valve. The system mayreceive, from the administrator via the remote communication receiver acontrol signal to reopen the valve despite the information about thepotential abnormal consumption, and reopen the valve.

The system may further receive from at least one sensor associated withthe distributed water infrastructure indications of regular water usage.The system may determine, from a plurality of indications received overa time period, a plurality of baseline water usage profiles. The systemmay receive from the at least one sensor a current water usage profile.The system may compare the current water usage profile with theplurality of baseline water usage profiles. The system may determine anwater abnormal consumption based on the comparison between the currentwater usage profile and the plurality of baseline water usage profiles.The system may generate an abnormal water consumption signal whenabnormal water consumption is determined. The system may receive, fromat least one sensor associated with the distributed waterinfrastructure, signals indicative of water usage in the distributedwater infrastructure. The system may determine, from the signalsindicative of water usage, a current water usage pattern.

The system may access a database of a plurality of stored water usagepatterns, where each at least one stored water usage pattern isassociated with at least one human health or lifestyle state. The systemmay compare at least one current water usage pattern with at least someof the stored water usage patterns. The system may, based on thecomparison, identify a human health or lifestyle condition reflected bythe current water usage pattern. The system may institute a remedialaction corresponding to the identified human health or lifestyle state.

In some embodiments, the system may receive, from a location in thedistributed water infrastructure upstream of the plurality of waterappliances, historical water usage measurements. The system maydetermine from the historical water usage measurements at least oneunique water usage signature associated with each of the plurality ofwater appliances. The system may store in memory each at least oneunique water usage signature for each of the plurality of appliances.The system may receive, from the location in the distributed waterinfrastructure upstream of the plurality of water appliances, currentwater usage measurements. The system may determine from the currentwater usage measurements at least one current water usage signature. Thesystem may compare the current water usage signature with at least oneof the unique water usage signatures stored in memory to determine amatch. The system may, based on the signature match, ascertain anidentifier of a water appliance in current use.

The system may receive water appliance usage data from the plurality ofgeographically distributed water sensors, where each water sensor islocated upstream of a plurality of water appliances in an associateddistributed water infrastructure, and where each water sensor isconfigured to collect data from an infrastructure inlet flow reflectiveof operation of at least one specific category of water appliancedownstream of the water sensor. The system may compare the waterappliance usage data from the plurality of geographically distributedwater sensors to determine trends in operation of the at least onespecific category of water appliance across a population. The system mayoutput information about the trends in operation. The system may detect,from at least one sensor in a distributed water infrastructure upstreamof the plurality of water appliances, a plurality of normal water usageprofiles. The system may associate at least one of the plurality ofnormal water usage profiles with each of the plurality of waterappliances. The system may store each of the plurality of normal waterusage profiles in a manner associating each of the plurality of normalwater usage profiles with an associated water appliance.

The system may detect at least one current water usage profile. Thesystem may compare the at least one current water usage profile with atleast one of the stored normal water usage profiles to determine acorresponding identity of an associated water usage appliance and todetermine if a substantial deviation exists between the stored normalwater usage profile for the identified appliance and the at least onecurrent water usage profile, where the substantial deviation isreflective of a potential malfunction in the associated water usageappliance. The system may initiate remedial action if the substantialdeviation, reflective of a potential malfunction, is determined.

The system may construct from signals indicative of water usage aplurality of water event profile signatures. The system may, based ondifferences between similar water event profiles, associate at least onewater event profile signature with a first water consumer and associatea second water event profile signature with a second water consumer. Thesystem may store the water event profile signatures for the first waterconsumer and the second water consumer. The system may construct currentwater event profiles reflecting subsequent water usage in thedistributed water infrastructure. The system may compare the currentwater event profiles with water event profile signatures stored inmemory. The system may, based on the comparison, attribute a firstcurrent water event profile to the first water consumer and attribute asecond current water event profile to the second water consumer. Thesystem may output data for generating at least one report of water usageby the first water consumer.

Accordingly, inventive concepts in the present disclosure may includesystems that feature combinations of elements and/or processing stepsfrom any and each disclosed embodiment, separately or in combination.Such modifications and combinations of the disclosed embodiments as wellas alternative embodiments of the inventions are expressly included inthis disclosure.

What is claimed is:
 1. A detection system for a distributed waterinfrastructure, wherein the system is configured to determine at leastone of a human health or lifestyle state from water usage patterns inthe distributed water infrastructure, the system comprising: at leastone processor configured to: receive from at least one sensor associatedwith the distributed water infrastructure signals indicative of waterusage in the distributed water infrastructure; determine from thesignals indicative of water usage a current water usage pattern; accessa database of a plurality of stored water usage patterns, wherein atleast one stored water usage pattern is associated with at least onehuman health or lifestyle state; compare at least one current waterusage pattern with at least some of the stored water usage patterns;based on the comparison, identify a human health or lifestyle conditionreflected by the current water usage pattern; and institute a remedialaction corresponding to the identified human health or lifestyle state;wherein the at least one processor is configured to receive an identityof the particular individual and to record water usage behavioralpatterns of the particular individual based on detection of the waterusage patterns; and wherein differing water usage patterns are storedfor differing numbers of individuals using the distributed water system,and wherein the processor is configured to at least generally determinea current number of individuals using the distributed water system andto select a stored water usage pattern for comparison purposes based onthe generally determined current number of individuals using thedistributed water system.
 2. A detection system for a distributed waterinfrastructure, wherein the system is configured to determine at leastone of a human health or lifestyle state from water usage patterns inthe distributed water infrastructure, the system comprising: at leastone processor configured to: receive from at least one sensor associatedwith the distributed water infrastructure signals indicative of waterusage in the distributed water infrastructure; determine from thesignals indicative of water usage a current water usage pattern; accessa database of a plurality of stored water usage patterns, wherein atleast one stored water usage pattern is associated with at least onehuman health or lifestyle state; compare at least one current waterusage pattern with at least one of the stored water usage patterns;based on the comparison, identify a human health or lifestyle statereflected by the current water usage pattern: and institute a remedialaction corresponding to the identified human health or lifestyle state,wherein the at least one processor is configured to determine based onat least one of the plurality of stored usage patterns a number oftoilet flushes above a threshold, wherein the associated health state isa digestive disorder, and wherein the remedial action is to send amessage indicating a probable digestive disorder.
 3. The system of claim2, wherein at least one stored water usage pattern is associated with atleast one particular appliance.
 4. The system of claim 3, wherein atleast one stored water usage pattern is associated with at least oneparticular individual.
 5. The system of claim 4, wherein the at leastone processor is configured to receive an identity of the at least oneparticular individual and to record water usage behavioral patterns ofthe at least one particular individual based on detection of the currentwater usage pattern.
 6. The system of claim 3, wherein the at least oneparticular appliance includes at least one of a washing machine, atoilet, and a dishwasher.
 7. The system of claim 2, wherein the healthor lifestyle state further includes a cognitive impairment and whereinthe remedial action includes sending an alert associated with thedetermined cognitive impairment.
 8. The system of claim 2, wherein theat least one processor is configured to identify based on the comparisona handwashing state, and wherein the remedial action includes storing arecord reflecting time spent handwashing.
 9. The system of claim 2,wherein at least two stored water usage patterns are associated with aparticular appliance.
 10. The system of claim 9, wherein the at leasttwo stored water usage patterns are associated with a faucet, andwherein a first water usage pattern corresponds to a duration of use ofthe faucet that is shorter than a duration of use associated with asecond water usage pattern.
 11. The system of claim 9, wherein a firstwater usage pattern corresponds to a shower, and the remedial actionincludes at least one of pulsing a valve to send a pulsed water signalto the shower, and recording a shower duration.
 12. The system of claim2, wherein the digestive disorder is a bowel irregularity.
 13. Thesystem of claim 2, wherein at least one stored water usage patternincludes at least a first pattern corresponding to toilet usage and asecond pattern corresponding to sink usage, and wherein the at least oneprocessor is configured to use the at least a first pattern and the atleast a second pattern to determine whether hands were washed followingtoilet usage.
 14. The system of claim 2, wherein at least one storedwater usage pattern reflects an extended period of non-water use,wherein the associated health state includes incapacity, and wherein theremedial action includes sending a message to a contact indicatinglikely incapacity.
 15. The system of claim 2, wherein at least onestored water usage pattern includes an amount of water usage below athreshold, wherein the associated health state includes unhealthiness,and wherein the remedial action includes sending a message to a remoterecipient indicating the probable unhealthiness.
 16. The system of claim2, wherein at least one stored water usage pattern reflects prolongedwater usage of an appliance beyond a threshold, wherein the associatedhealth state includes dementia, and wherein the remedial action includessending a message indicating a probability of dementia.
 17. The systemof claim 2, wherein at least one stored water usage pattern reflectsprolonged water usage of an appliance beyond a threshold, wherein theassociated health state includes an injury, and wherein the remedialaction includes contacting emergency services.
 18. The system of claim2, wherein the at least one processor is further configured to determinefrom the current water usage pattern when an inhabitant is likely awayfrom home and the remedial action includes sending an alert relating towater usage during an away period.
 19. The system of claim 2, whereinthe at least one sensor has a resolution of at least 1 liter per hour.20. The system of claim 2, wherein the at least one processor is furtherconfigured to determine from an increased frequency of water usagepatterns that an increased number of users are using the system, andsend an alert.